--- title: RheoData Blog | 21c description: 21c | RheoData Blog Posts --- [![RheoData - Logo - transparent-1](https://rheodata.com/hs-fs/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png?width=250&height=50&name=RheoData%20-%20Logo%20-%20transparent-1.png "RheoData - Logo - transparent-1")](https://rheodata.com/) - Who We Are - [About Us](https://rheodata.com/who-we-are) - Services - Consulting - [The Studio](https://rheodata.com/the-studio) - Accelerators - [FrostCore](https://rheodata.com/frostcore) - [FrostAI](https://rheodata.com/frostai) - [RedCore](https://rheodata.com/redcore) - [RedAI](https://rheodata.com/redai) - [RedGuard](https://rheodata.com/redguard) - [BlueCore](https://rheodata.com/bluecore) - [Calypso](https://rheodata.com/calypso) - Services - [Data Integration](https://rheodata.com/data-integration) - [Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) [![](https://rheodata.com/hs-fs/hubfs/Imported_Blog_Media/blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png?width=100&height=100&name=blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png)](https://rheodata.com/) [![RheoData - Logo - transparent-1](https://rheodata.com/hs-fs/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png?width=250&height=50&name=RheoData%20-%20Logo%20-%20transparent-1.png "RheoData - Logo - transparent-1")](https://rheodata.com/) - Who We Are - [About Us](https://rheodata.com/who-we-are) - Services - Consulting - [The Studio](https://rheodata.com/the-studio) - Accelerators - [FrostCore](https://rheodata.com/frostcore) - [FrostAI](https://rheodata.com/frostai) - [RedCore](https://rheodata.com/redcore) - [RedAI](https://rheodata.com/redai) - [RedGuard](https://rheodata.com/redguard) - [BlueCore](https://rheodata.com/bluecore) - [Calypso](https://rheodata.com/calypso) - Services - [Data Integration](https://rheodata.com/data-integration) - [Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) [![](https://rheodata.com/hs-fs/hubfs/Imported_Blog_Media/blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png?width=100&height=100&name=blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png)](https://rheodata.com/) - Who We Are - [About Us](https://rheodata.com/who-we-are) - Services - Consulting - [The Studio](https://rheodata.com/the-studio) - Accelerators - [FrostCore](https://rheodata.com/frostcore) - [FrostAI](https://rheodata.com/frostai) - [RedCore](https://rheodata.com/redcore) - [RedAI](https://rheodata.com/redai) - [RedGuard](https://rheodata.com/redguard) - [BlueCore](https://rheodata.com/bluecore) - [Calypso](https://rheodata.com/calypso) - Services - [Data Integration](https://rheodata.com/data-integration) - [Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) Posts about # 21c ## [Basic DDL Replication with Oracle GoldenGate](https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate) Posted by [Fame](https://rheodata.com/en-us/blog/author/fame) | Nov 10, 2025 9:31:00 PM With any type of replication configuration or replication tool, primary purpose is to move the data... [CONTINUE READING](https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate) ## [Deploying Oracle GoldenGate 21c with Ansible](https://rheodata.com/en-us/blog/deploying-oracle-goldengate-21c-with-ansible) Posted by [Fame](https://rheodata.com/en-us/blog/author/fame) | Nov 10, 2025 9:30:52 PM Ansible has become a standard configuration tool for many enterprises and is used is many CI/CD... [CONTINUE READING](https://rheodata.com/en-us/blog/deploying-oracle-goldengate-21c-with-ansible) ## [Configuring Nginx on RedHat Linux 7.9 for Oracle GoldenGate 21c](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c-2) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:09 PM When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number... [CONTINUE READING](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c-2) ## [Identifying Predefined Administrative Accounts in Autonomous Database or any other Oracle database](https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:08 PM A quick post as a reminder for myself some time down the road. After all, we all need reminders... [CONTINUE READING](https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database) ## [Configure Oracle GoldenGate’s ServiceManager as a Linux Service](https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service) Posted by [rheostage5132](https://rheodata.com/en-us/blog/author/rheostage5132) | Nov 10, 2025 9:30:06 PM After installing Oracle GoldenGate with a manual ServiceManager, you realize that the... [CONTINUE READING](https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service) ## [Configuring Nginx on AWS EC2 for Oracle GoldenGate 21c](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:01 PM When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number... [CONTINUE READING](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c) ## [The transition has begun … Oracle GoldenGate merging into Oracle Database 21 (new features)](https://rheodata.com/en-us/blog/the-transition-has-begun-oracle-goldengate-merging-into-oracle-database-21-new-features) Posted by [rheostage5132](https://rheodata.com/en-us/blog/author/rheostage5132) | Nov 10, 2025 9:29:58 PM News on the Oracle GoldenGate front!!!!! [CONTINUE READING](https://rheodata.com/en-us/blog/the-transition-has-begun-oracle-goldengate-merging-into-oracle-database-21-new-features) ## [Modern Data Platform with Oracle Cloud Infrastructure (OCI)](https://rheodata.com/en-us/blog/moder-data-platform) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:29:41 PM Does data drive your organization? Have you started your transition to a Modern Data Platform? Does... [CONTINUE READING](https://rheodata.com/en-us/blog/moder-data-platform) ## [Data Pipelines – What is a data pipeline?](https://rheodata.com/en-us/blog/data-pipelines) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:29:37 PM A data pipeline is a method in which raw data or unchanged data is ingested from various data... [CONTINUE READING](https://rheodata.com/en-us/blog/data-pipelines) ## [Interesting change in ALTER EXTRACT command](https://rheodata.com/en-us/blog/alter-extract-command) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:29:34 PM Today, while helping a customer, we had to rebuild an extract. The integrated extract that we... [CONTINUE READING](https://rheodata.com/en-us/blog/alter-extract-command) ### Recent Posts #### [Coordinated Replicats: Faster, Lower-Risk GoldenGate Loads](https://rheodata.com/en-us/blog/coordinated-replicats-initial-load) Posted at Jun 26, 2026 11:08:13 AM ![Post Featured Image](https://rheodata.com/hubfs/Gemini_Generated_Image_509fjc509fjc509f.png) #### [Forward Deployed Engineering: The Operating Model the Agentic Era Demands](https://rheodata.com/en-us/blog/forward-deployed-engineering-agentic-era) Posted at May 30, 2026 11:46:34 AM ![Post Featured Image](https://rheodata.com/hubfs/Gemini_Generated_Image_r8vpntr8vpntr8vp.png) #### [The Bowl Is Broken: A CEO's Note on Mental Health Month and Tech Team Burnout](https://rheodata.com/en-us/blog/tech-team-burnout-mental-health-month-2026) Posted at May 12, 2026 7:23:33 AM ![Post Featured Image](https://rheodata.com/hubfs/IMG_2142.jpg) ### Posts by Tag - [Cloud (88)](https://rheodata.com/en-us/blog/tag/cloud) - [GoldenGate (73)](https://rheodata.com/en-us/blog/tag/goldengate) - [Business Insights (51)](https://rheodata.com/en-us/blog/tag/business-insights) - [AI (36)](https://rheodata.com/en-us/blog/tag/ai) - [19c (22)](https://rheodata.com/en-us/blog/tag/19c) - [ai pipelines (17)](https://rheodata.com/en-us/blog/tag/ai-pipelines) - [18c (15)](https://rheodata.com/en-us/blog/tag/18c) - [21c (14)](https://rheodata.com/en-us/blog/tag/21c) - [12c (11)](https://rheodata.com/en-us/blog/tag/12c) - [machine learning (10)](https://rheodata.com/en-us/blog/tag/machine-learning) - [23ai (9)](https://rheodata.com/en-us/blog/tag/23ai) - [database (9)](https://rheodata.com/en-us/blog/tag/database) - [goldengate 21c (9)](https://rheodata.com/en-us/blog/tag/goldengate-21c) - [artificial intelligence (8)](https://rheodata.com/en-us/blog/tag/artificial-intelligence) - [data analytics (8)](https://rheodata.com/en-us/blog/tag/data-analytics) - [Google (7)](https://rheodata.com/en-us/blog/tag/google) - [23ai AI vector search (6)](https://rheodata.com/en-us/blog/tag/23ai-ai-vector-search) - [aws ec2 (6)](https://rheodata.com/en-us/blog/tag/aws-ec2) - [aws ec2 compute (6)](https://rheodata.com/en-us/blog/tag/aws-ec2-compute) - [ec2 (6)](https://rheodata.com/en-us/blog/tag/ec2) - [ggs (6)](https://rheodata.com/en-us/blog/tag/ggs) - [goldengate 19c (6)](https://rheodata.com/en-us/blog/tag/goldengate-19c) - [install nginx (6)](https://rheodata.com/en-us/blog/tag/install-nginx) - [23.4 (5)](https://rheodata.com/en-us/blog/tag/23-4) - [AI Vector Search (5)](https://rheodata.com/en-us/blog/tag/ai-vector-search) - [analytics (5)](https://rheodata.com/en-us/blog/tag/analytics) - [classic to microservices (5)](https://rheodata.com/en-us/blog/tag/classic-to-microservices) - [cloud-migration (5)](https://rheodata.com/en-us/blog/tag/cloud-migration) - [data mesh (5)](https://rheodata.com/en-us/blog/tag/data-mesh) - [database migration (5)](https://rheodata.com/en-us/blog/tag/database-migration) - [goldengate microservices (5)](https://rheodata.com/en-us/blog/tag/goldengate-microservices) - [11g (4)](https://rheodata.com/en-us/blog/tag/11g) - [19c goldengate (4)](https://rheodata.com/en-us/blog/tag/19c-goldengate) - [Azure (4)](https://rheodata.com/en-us/blog/tag/azure) - [Database Modernization (4)](https://rheodata.com/en-us/blog/tag/database-modernization) - [Google Cloud (4)](https://rheodata.com/en-us/blog/tag/google-cloud) - [Oracle GoldenGate (4)](https://rheodata.com/en-us/blog/tag/oracle-goldengate) - [autonomous database (4)](https://rheodata.com/en-us/blog/tag/autonomous-database) - [cloud management (4)](https://rheodata.com/en-us/blog/tag/cloud-management) - [cloud services (4)](https://rheodata.com/en-us/blog/tag/cloud-services) - [data engineering (4)](https://rheodata.com/en-us/blog/tag/data-engineering) - [data engineers (4)](https://rheodata.com/en-us/blog/tag/data-engineers) - [data governance (4)](https://rheodata.com/en-us/blog/tag/data-governance) - [heatwave (4)](https://rheodata.com/en-us/blog/tag/heatwave) - [12.2.1.x (3)](https://rheodata.com/en-us/blog/tag/12-2-1-x) - [12.3.x (3)](https://rheodata.com/en-us/blog/tag/12-3-x) - [12c goldengate (3)](https://rheodata.com/en-us/blog/tag/12c-goldengate) - [18c goldengate (3)](https://rheodata.com/en-us/blog/tag/18c-goldengate) - [23c (3)](https://rheodata.com/en-us/blog/tag/23c) - [AI Integration (3)](https://rheodata.com/en-us/blog/tag/ai-integration) - [Database Administration (3)](https://rheodata.com/en-us/blog/tag/database-administration) - [GoldenGate 23c (3)](https://rheodata.com/en-us/blog/tag/goldengate-23c) - [MySQL (3)](https://rheodata.com/en-us/blog/tag/mysql) - [Oracle Cloud Migration (3)](https://rheodata.com/en-us/blog/tag/oracle-cloud-migration) - [Oracle Database 26ai (3)](https://rheodata.com/en-us/blog/tag/oracle-database-26ai) - [adminclient (3)](https://rheodata.com/en-us/blog/tag/adminclient) - [architecture of data pipelines (3)](https://rheodata.com/en-us/blog/tag/architecture-of-data-pipelines) - [automation (3)](https://rheodata.com/en-us/blog/tag/automation) - [batch processing (3)](https://rheodata.com/en-us/blog/tag/batch-processing) - [big data (3)](https://rheodata.com/en-us/blog/tag/big-data) - [data cleaning (3)](https://rheodata.com/en-us/blog/tag/data-cleaning) - [data integration (3)](https://rheodata.com/en-us/blog/tag/data-integration) - [data pipelines (3)](https://rheodata.com/en-us/blog/tag/data-pipelines) - [data pipelines vs ETL pipelines (3)](https://rheodata.com/en-us/blog/tag/data-pipelines-vs-etl-pipelines) - [data science (3)](https://rheodata.com/en-us/blog/tag/data-science) - [data-replication (3)](https://rheodata.com/en-us/blog/tag/data-replication) - [database-platforms (3)](https://rheodata.com/en-us/blog/tag/database-platforms) - [enterprise data replication (3)](https://rheodata.com/en-us/blog/tag/enterprise-data-replication) - [gcp (3)](https://rheodata.com/en-us/blog/tag/gcp) - [hashicorp vault enterprise (3)](https://rheodata.com/en-us/blog/tag/hashicorp-vault-enterprise) - [Agentic AI (2)](https://rheodata.com/en-us/blog/tag/agentic-ai) - [Bring Your Own License (BYOL) Oracle (2)](https://rheodata.com/en-us/blog/tag/bring-your-own-license-byol-oracle) - [Cloud Database (2)](https://rheodata.com/en-us/blog/tag/cloud-database) - [Cloud modernization strategy (2)](https://rheodata.com/en-us/blog/tag/cloud-modernization-strategy) - [Docker (2)](https://rheodata.com/en-us/blog/tag/docker) - [EnterpriseDB (2)](https://rheodata.com/en-us/blog/tag/enterprisedb) - [Flask (2)](https://rheodata.com/en-us/blog/tag/flask) - [Google Cloud for Oracle workloads (2)](https://rheodata.com/en-us/blog/tag/google-cloud-for-oracle-workloads) - [Legacy Oracle systems (2)](https://rheodata.com/en-us/blog/tag/legacy-oracle-systems) - [Oracle AI Vector Search (2)](https://rheodata.com/en-us/blog/tag/oracle-ai-vector-search) - [Oracle Cloud Infrastructure (2)](https://rheodata.com/en-us/blog/tag/oracle-cloud-infrastructure) - [Oracle DBA skills in the cloud (2)](https://rheodata.com/en-us/blog/tag/oracle-dba-skills-in-the-cloud) - [Oracle GoldenGate 23ai (2)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-23ai) - [Oracle migration assessment (2)](https://rheodata.com/en-us/blog/tag/oracle-migration-assessment) - [Oracle on GCP (2)](https://rheodata.com/en-us/blog/tag/oracle-on-gcp) - [Snowflake (2)](https://rheodata.com/en-us/blog/tag/snowflake) - [Snowflake cost optimization (2)](https://rheodata.com/en-us/blog/tag/snowflake-cost-optimization) - [aws (2)](https://rheodata.com/en-us/blog/tag/aws) - [azure ai studio (2)](https://rheodata.com/en-us/blog/tag/azure-ai-studio) - [build mysql heatwave (2)](https://rheodata.com/en-us/blog/tag/build-mysql-heatwave) - [cloud dba (2)](https://rheodata.com/en-us/blog/tag/cloud-dba) - [cloud ready (2)](https://rheodata.com/en-us/blog/tag/cloud-ready) - [cohere generate documentation (2)](https://rheodata.com/en-us/blog/tag/cohere-generate-documentation) - [data-pipeline (2)](https://rheodata.com/en-us/blog/tag/data-pipeline) - [database replication security (2)](https://rheodata.com/en-us/blog/tag/database-replication-security) - [deployment (2)](https://rheodata.com/en-us/blog/tag/deployment) - [docker adminclient (2)](https://rheodata.com/en-us/blog/tag/docker-adminclient) - [golden gate (2)](https://rheodata.com/en-us/blog/tag/golden-gate) - [goldengate cloud (2)](https://rheodata.com/en-us/blog/tag/goldengate-cloud) - [goldengate migrations (2)](https://rheodata.com/en-us/blog/tag/goldengate-migrations) - [goldengate parameter files (2)](https://rheodata.com/en-us/blog/tag/goldengate-parameter-files) - [google postgresql migration (2)](https://rheodata.com/en-us/blog/tag/google-postgresql-migration) - [ml (2)](https://rheodata.com/en-us/blog/tag/ml) - [real-time data replication (2)](https://rheodata.com/en-us/blog/tag/real-time-data-replication) - [0.12upgrade (1)](https://rheodata.com/en-us/blog/tag/0-12upgrade) - [11.2.0.4 (1)](https://rheodata.com/en-us/blog/tag/11-2-0-4) - [11g to 19c (1)](https://rheodata.com/en-us/blog/tag/11g-to-19c) - [11g to 21c (1)](https://rheodata.com/en-us/blog/tag/11g-to-21c) - [11g to 23c (1)](https://rheodata.com/en-us/blog/tag/11g-to-23c) - [11g to OCI (1)](https://rheodata.com/en-us/blog/tag/11g-to-oci) - [19.1.0.0.0 (1)](https://rheodata.com/en-us/blog/tag/19-1-0-0-0) - [19.1.0.0.1 (1)](https://rheodata.com/en-us/blog/tag/19-1-0-0-1) - [2024 (1)](https://rheodata.com/en-us/blog/tag/2024) - [5.7 (1)](https://rheodata.com/en-us/blog/tag/5-7) - [5.7 to 8.0 (1)](https://rheodata.com/en-us/blog/tag/5-7-to-8-0) - [8.0 (1)](https://rheodata.com/en-us/blog/tag/8-0) - [AI Agents (1)](https://rheodata.com/en-us/blog/tag/ai-agents) - [AI Data Platform (1)](https://rheodata.com/en-us/blog/tag/ai-data-platform) - [AI Infrastructure Management (1)](https://rheodata.com/en-us/blog/tag/ai-infrastructure-management) - [AI Machine Learning (1)](https://rheodata.com/en-us/blog/tag/ai-machine-learning) - [AI blog writing (1)](https://rheodata.com/en-us/blog/tag/ai-blog-writing) - [AI business productivity (1)](https://rheodata.com/en-us/blog/tag/ai-business-productivity) - [AI content creation (1)](https://rheodata.com/en-us/blog/tag/ai-content-creation) - [AI data infrastructure (1)](https://rheodata.com/en-us/blog/tag/ai-data-infrastructure) - [AI data management (1)](https://rheodata.com/en-us/blog/tag/ai-data-management) - [AI data platform optimization (1)](https://rheodata.com/en-us/blog/tag/ai-data-platform-optimization) - [AI database administration (1)](https://rheodata.com/en-us/blog/tag/ai-database-administration) - [AI database management tools (1)](https://rheodata.com/en-us/blog/tag/ai-database-management-tools) - [AI ethics content (1)](https://rheodata.com/en-us/blog/tag/ai-ethics-content) - [AI governance (1)](https://rheodata.com/en-us/blog/tag/ai-governance) - [AI inference bottlenecks (1)](https://rheodata.com/en-us/blog/tag/ai-inference-bottlenecks) - [AI model deployment strategies (1)](https://rheodata.com/en-us/blog/tag/ai-model-deployment-strategies) - [AI security (1)](https://rheodata.com/en-us/blog/tag/ai-security) - [AI writing tools (1)](https://rheodata.com/en-us/blog/tag/ai-writing-tools) - [AI-Driven-Revenue-Growth (1)](https://rheodata.com/en-us/blog/tag/ai-driven-revenue-growth) - [AI-Native Applications (1)](https://rheodata.com/en-us/blog/tag/ai-native-applications) - [AI-ROI (1)](https://rheodata.com/en-us/blog/tag/ai-roi) - [AI-Ready Data (1)](https://rheodata.com/en-us/blog/tag/ai-ready-data) - [AI-accuracy (1)](https://rheodata.com/en-us/blog/tag/ai-accuracy) - [AI-compliance (1)](https://rheodata.com/en-us/blog/tag/ai-compliance) - [AI-hallucination-prevention (1)](https://rheodata.com/en-us/blog/tag/ai-hallucination-prevention) - [AI-powered database replication management (1)](https://rheodata.com/en-us/blog/tag/ai-powered-database-replication-management) - [API authentication (1)](https://rheodata.com/en-us/blog/tag/api-authentication) - [AWS S3 (1)](https://rheodata.com/en-us/blog/tag/aws-s3) - [Apache Iceberg (1)](https://rheodata.com/en-us/blog/tag/apache-iceberg) - [Apache Spark data platform (1)](https://rheodata.com/en-us/blog/tag/apache-spark-data-platform) - [Atlanta database consultants (1)](https://rheodata.com/en-us/blog/tag/atlanta-database-consultants) - [Azure Data Lake (1)](https://rheodata.com/en-us/blog/tag/azure-data-lake) - [Big Query (1)](https://rheodata.com/en-us/blog/tag/big-query) - [BigQuery Integration (1)](https://rheodata.com/en-us/blog/tag/bigquery-integration) - [Business-Intelligence-Modernization (1)](https://rheodata.com/en-us/blog/tag/business-intelligence-modernization) - [CLOB to VARCHAR (1)](https://rheodata.com/en-us/blog/tag/clob-to-varchar) - [Change Data Capture GoldenGate Extract (1)](https://rheodata.com/en-us/blog/tag/change-data-capture-goldengate-extract) - [Cloud Data Platform (1)](https://rheodata.com/en-us/blog/tag/cloud-data-platform) - [Cloud database migration (1)](https://rheodata.com/en-us/blog/tag/cloud-database-migration) - [Coordinated Replicat (1)](https://rheodata.com/en-us/blog/tag/coordinated-replicat) - [Cortex Agents (1)](https://rheodata.com/en-us/blog/tag/cortex-agents) - [Cosine distance Oracle (1)](https://rheodata.com/en-us/blog/tag/cosine-distance-oracle) - [Cross-platform data monitoring (1)](https://rheodata.com/en-us/blog/tag/cross-platform-data-monitoring) - [Customer-Experience-Optimization (1)](https://rheodata.com/en-us/blog/tag/customer-experience-optimization) - [DBA burnout prevention (1)](https://rheodata.com/en-us/blog/tag/dba-burnout-prevention) - [DBA productivity (1)](https://rheodata.com/en-us/blog/tag/dba-productivity) - [DBA skills AI (1)](https://rheodata.com/en-us/blog/tag/dba-skills-ai) - [Data Modernization (1)](https://rheodata.com/en-us/blog/tag/data-modernization) - [Data Pipeline Architecture (1)](https://rheodata.com/en-us/blog/tag/data-pipeline-architecture) - [Data Pipeline Management (1)](https://rheodata.com/en-us/blog/tag/data-pipeline-management) - [Data Streaming (1)](https://rheodata.com/en-us/blog/tag/data-streaming) - [Data Transformation (1)](https://rheodata.com/en-us/blog/tag/data-transformation) - [Data pipeline troubleshooting (1)](https://rheodata.com/en-us/blog/tag/data-pipeline-troubleshooting) - [Database Security (1)](https://rheodata.com/en-us/blog/tag/database-security) - [Database lag monitoring (1)](https://rheodata.com/en-us/blog/tag/database-lag-monitoring) - [Database migration strategy (1)](https://rheodata.com/en-us/blog/tag/database-migration-strategy) - [Database migration vs. replication (1)](https://rheodata.com/en-us/blog/tag/database-migration-vs-replication) - [Database replication blind spots (1)](https://rheodata.com/en-us/blog/tag/database-replication-blind-spots) - [Database replication monitoring (1)](https://rheodata.com/en-us/blog/tag/database-replication-monitoring) - [Database replication performance monitoring (1)](https://rheodata.com/en-us/blog/tag/database-replication-performance-monitoring) - [Databricks comparison (1)](https://rheodata.com/en-us/blog/tag/databricks-comparison) - [Delta Lake integration (1)](https://rheodata.com/en-us/blog/tag/delta-lake-integration) - [Digital-Transformation-ROI (1)](https://rheodata.com/en-us/blog/tag/digital-transformation-roi) - [EXTFILE (1)](https://rheodata.com/en-us/blog/tag/extfile) - [EXTRAIL (1)](https://rheodata.com/en-us/blog/tag/extrail) - [Edge computing AI (1)](https://rheodata.com/en-us/blog/tag/edge-computing-ai) - [Enterprise AI Strategy (1)](https://rheodata.com/en-us/blog/tag/enterprise-ai-strategy) - [Enterprise AI scalability (1)](https://rheodata.com/en-us/blog/tag/enterprise-ai-scalability) - [Enterprise cloud migration (1)](https://rheodata.com/en-us/blog/tag/enterprise-cloud-migration) - [Enterprise data migration (1)](https://rheodata.com/en-us/blog/tag/enterprise-data-migration) - [Enterprise database replication monitoring (1)](https://rheodata.com/en-us/blog/tag/enterprise-database-replication-monitoring) - [Forward Deployed Engineering (1)](https://rheodata.com/en-us/blog/tag/forward-deployed-engineering) - [GPU memory optimization (1)](https://rheodata.com/en-us/blog/tag/gpu-memory-optimization) - [GUI (1)](https://rheodata.com/en-us/blog/tag/gui) - [Gemini Enterprise (1)](https://rheodata.com/en-us/blog/tag/gemini-enterprise) - [GoldenGate 21c upgrade (1)](https://rheodata.com/en-us/blog/tag/goldengate-21c-upgrade) - [GoldenGate 23ai to 26ai (1)](https://rheodata.com/en-us/blog/tag/goldengate-23ai-to-26ai) - [GoldenGate 26ai new features (1)](https://rheodata.com/en-us/blog/tag/goldengate-26ai-new-features) - [GoldenGate 26ai release notes (1)](https://rheodata.com/en-us/blog/tag/goldengate-26ai-release-notes) - [GoldenGate 26ai upgrade (1)](https://rheodata.com/en-us/blog/tag/goldengate-26ai-upgrade) - [GoldenGate AI integration (1)](https://rheodata.com/en-us/blog/tag/goldengate-ai-integration) - [GoldenGate CDC configuration (1)](https://rheodata.com/en-us/blog/tag/goldengate-cdc-configuration) - [GoldenGate DAA (1)](https://rheodata.com/en-us/blog/tag/goldengate-daa) - [GoldenGate Extract user permissions (1)](https://rheodata.com/en-us/blog/tag/goldengate-extract-user-permissions) - [GoldenGate Yugabyte support (1)](https://rheodata.com/en-us/blog/tag/goldengate-yugabyte-support) - [GoldenGate certificate authentication (1)](https://rheodata.com/en-us/blog/tag/goldengate-certificate-authentication) - [GoldenGate cutover planning (1)](https://rheodata.com/en-us/blog/tag/goldengate-cutover-planning) - [GoldenGate deployment automation (1)](https://rheodata.com/en-us/blog/tag/goldengate-deployment-automation) - [GoldenGate granular permissions setup (1)](https://rheodata.com/en-us/blog/tag/goldengate-granular-permissions-setup) - [GoldenGate least privilege security (1)](https://rheodata.com/en-us/blog/tag/goldengate-least-privilege-security) - [GoldenGate lifecycle management (1)](https://rheodata.com/en-us/blog/tag/goldengate-lifecycle-management) - [GoldenGate migration guide (1)](https://rheodata.com/en-us/blog/tag/goldengate-migration-guide) - [GoldenGate migration sizing (1)](https://rheodata.com/en-us/blog/tag/goldengate-migration-sizing) - [GoldenGate monitoring and lag management (1)](https://rheodata.com/en-us/blog/tag/goldengate-monitoring-and-lag-management) - [GoldenGate operational ownership (1)](https://rheodata.com/en-us/blog/tag/goldengate-operational-ownership) - [GoldenGate password management (1)](https://rheodata.com/en-us/blog/tag/goldengate-password-management) - [GoldenGate port configuration (1)](https://rheodata.com/en-us/blog/tag/goldengate-port-configuration) - [GoldenGate replication lag detection (1)](https://rheodata.com/en-us/blog/tag/goldengate-replication-lag-detection) - [GoldenGate response file (1)](https://rheodata.com/en-us/blog/tag/goldengate-response-file) - [GoldenGate trail file management (1)](https://rheodata.com/en-us/blog/tag/goldengate-trail-file-management) - [GoldenGate troubleshooting solutions (1)](https://rheodata.com/en-us/blog/tag/goldengate-troubleshooting-solutions) - [GoldenGate unified console (1)](https://rheodata.com/en-us/blog/tag/goldengate-unified-console) - [GoldenGateMCP (1)](https://rheodata.com/en-us/blog/tag/goldengatemcp) - [Google Cloud Platform (1)](https://rheodata.com/en-us/blog/tag/google-cloud-platform) - [Google Cloud Storage (1)](https://rheodata.com/en-us/blog/tag/google-cloud-storage) - [Google-AlloyDB (1)](https://rheodata.com/en-us/blog/tag/google-alloydb) - [HashiCorp (1)](https://rheodata.com/en-us/blog/tag/hashicorp) - [Hybrid queries Oracle (1)](https://rheodata.com/en-us/blog/tag/hybrid-queries-oracle) - [IT cost optimization (1)](https://rheodata.com/en-us/blog/tag/it-cost-optimization) - [IT infrastructure simplification (1)](https://rheodata.com/en-us/blog/tag/it-infrastructure-simplification) - [IT leadership mental health (1)](https://rheodata.com/en-us/blog/tag/it-leadership-mental-health) - [Initial Load (1)](https://rheodata.com/en-us/blog/tag/initial-load) - [Inventory management data lag (1)](https://rheodata.com/en-us/blog/tag/inventory-management-data-lag) - [LLM inference optimization (1)](https://rheodata.com/en-us/blog/tag/llm-inference-optimization) - [Large language model performance (1)](https://rheodata.com/en-us/blog/tag/large-language-model-performance) - [MCP Server for Oracle (1)](https://rheodata.com/en-us/blog/tag/mcp-server-for-oracle) - [MCP Server, (1)](https://rheodata.com/en-us/blog/tag/mcp-server) - [Mental Health Awareness Month tech industry (1)](https://rheodata.com/en-us/blog/tag/mental-health-awareness-month-tech-industry) - [Migration readiness (1)](https://rheodata.com/en-us/blog/tag/migration-readiness) - [Model Context Protocol (1)](https://rheodata.com/en-us/blog/tag/model-context-protocol) - [Model inference costs (1)](https://rheodata.com/en-us/blog/tag/model-inference-costs) - [OMA assessment (1)](https://rheodata.com/en-us/blog/tag/oma-assessment) - [ONNX embedding model Oracle (1)](https://rheodata.com/en-us/blog/tag/onnx-embedding-model-oracle) - [Operating Model (1)](https://rheodata.com/en-us/blog/tag/operating-model) - [Oracle 23ai features (1)](https://rheodata.com/en-us/blog/tag/oracle-23ai-features) - [Oracle 26ai features (1)](https://rheodata.com/en-us/blog/tag/oracle-26ai-features) - [Oracle AI Data Platform (1)](https://rheodata.com/en-us/blog/tag/oracle-ai-data-platform) - [Oracle AI Solutions (1)](https://rheodata.com/en-us/blog/tag/oracle-ai-solutions) - [Oracle Autonomous Database migration (1)](https://rheodata.com/en-us/blog/tag/oracle-autonomous-database-migration) - [Oracle CPAT vs OMA comparison (1)](https://rheodata.com/en-us/blog/tag/oracle-cpat-vs-oma-comparison) - [Oracle Database 23ai vectors (1)](https://rheodata.com/en-us/blog/tag/oracle-database-23ai-vectors) - [Oracle Database 26ai vectors (1)](https://rheodata.com/en-us/blog/tag/oracle-database-26ai-vectors) - [Oracle EBS migration (1)](https://rheodata.com/en-us/blog/tag/oracle-ebs-migration) - [Oracle Exadata on Google Cloud (1)](https://rheodata.com/en-us/blog/tag/oracle-exadata-on-google-cloud) - [Oracle GoldenGate 26ai (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-26ai) - [Oracle GoldenGate AI diagnostics (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-ai-diagnostics) - [Oracle GoldenGate Azure (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-azure) - [Oracle GoldenGate Management (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-management) - [Oracle GoldenGate REST API automation (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-rest-api-automation) - [Oracle GoldenGate SQL Server permissions (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-sql-server-permissions) - [Oracle GoldenGate automation (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-automation) - [Oracle GoldenGate heartbeat (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-heartbeat) - [Oracle GoldenGate least privilege security (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-least-privilege-security) - [Oracle GoldenGate managed services (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-managed-services) - [Oracle GoldenGate migration strategy (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-migration-strategy) - [Oracle GoldenGate monitoring tools (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-monitoring-tools) - [Oracle GoldenGate replication best practices (1)](https://rheodata.com/en-us/blog/tag/oracle-goldengate-replication-best-practices) - [Oracle and Google Cloud AI (1)](https://rheodata.com/en-us/blog/tag/oracle-and-google-cloud-ai) - [Oracle cloud cost optimization (1)](https://rheodata.com/en-us/blog/tag/oracle-cloud-cost-optimization) - [Oracle cloud migration assessment (1)](https://rheodata.com/en-us/blog/tag/oracle-cloud-migration-assessment) - [Oracle data replication 2026 (1)](https://rheodata.com/en-us/blog/tag/oracle-data-replication-2026) - [Oracle data replication compliance (1)](https://rheodata.com/en-us/blog/tag/oracle-data-replication-compliance) - [Oracle database migration to OCI (1)](https://rheodata.com/en-us/blog/tag/oracle-database-migration-to-oci) - [Oracle replication governance (1)](https://rheodata.com/en-us/blog/tag/oracle-replication-governance) - [Oracle replication lag diagnosis (1)](https://rheodata.com/en-us/blog/tag/oracle-replication-lag-diagnosis) - [Oracle to cloud migration (1)](https://rheodata.com/en-us/blog/tag/oracle-to-cloud-migration) - [Oracle vs Databricks (1)](https://rheodata.com/en-us/blog/tag/oracle-vs-databricks) - [Oracle workload analysis (1)](https://rheodata.com/en-us/blog/tag/oracle-workload-analysis) - [Oracle@Google Cloud (1)](https://rheodata.com/en-us/blog/tag/oraclegoogle-cloud) - [Parallel Replicat (1)](https://rheodata.com/en-us/blog/tag/parallel-replicat) - [Parquet (1)](https://rheodata.com/en-us/blog/tag/parquet) - [RAG pipeline database (1)](https://rheodata.com/en-us/blog/tag/rag-pipeline-database) - [REST API (1)](https://rheodata.com/en-us/blog/tag/rest-api) - [Real-time AI processing (1)](https://rheodata.com/en-us/blog/tag/real-time-ai-processing) - [SQL Server replication security best practices (1)](https://rheodata.com/en-us/blog/tag/sql-server-replication-security-best-practices) - [Semantic search database (1)](https://rheodata.com/en-us/blog/tag/semantic-search-database) - [Similarity search Oracle (1)](https://rheodata.com/en-us/blog/tag/similarity-search-oracle) - [Snowflake Optima indexing (1)](https://rheodata.com/en-us/blog/tag/snowflake-optima-indexing) - [Snowflake Search Optimization Service (1)](https://rheodata.com/en-us/blog/tag/snowflake-search-optimization-service) - [Snowflake alternatives (1)](https://rheodata.com/en-us/blog/tag/snowflake-alternatives) - [Snowflake automatic clustering (1)](https://rheodata.com/en-us/blog/tag/snowflake-automatic-clustering) - [Snowflake budget monitoring (1)](https://rheodata.com/en-us/blog/tag/snowflake-budget-monitoring) - [Snowflake cloud data warehouse performance (1)](https://rheodata.com/en-us/blog/tag/snowflake-cloud-data-warehouse-performance) - [Snowflake cost governance (1)](https://rheodata.com/en-us/blog/tag/snowflake-cost-governance) - [Snowflake cost management (1)](https://rheodata.com/en-us/blog/tag/snowflake-cost-management) - [Snowflake cost reduction strategies (1)](https://rheodata.com/en-us/blog/tag/snowflake-cost-reduction-strategies) - [Snowflake credit usage (1)](https://rheodata.com/en-us/blog/tag/snowflake-credit-usage) - [Snowflake materialized views (1)](https://rheodata.com/en-us/blog/tag/snowflake-materialized-views) - [Snowflake migration staffing (1)](https://rheodata.com/en-us/blog/tag/snowflake-migration-staffing) - [Snowflake performance optimization (1)](https://rheodata.com/en-us/blog/tag/snowflake-performance-optimization) - [Snowflake query acceleration service (1)](https://rheodata.com/en-us/blog/tag/snowflake-query-acceleration-service) - [Snowflake query performance tuning (1)](https://rheodata.com/en-us/blog/tag/snowflake-query-performance-tuning) - [Snowflake resource monitors (1)](https://rheodata.com/en-us/blog/tag/snowflake-resource-monitors) - [Snowflake serverless compute costs (1)](https://rheodata.com/en-us/blog/tag/snowflake-serverless-compute-costs) - [Snowflake spend attribution (1)](https://rheodata.com/en-us/blog/tag/snowflake-spend-attribution) - [Snowflake warehouse optimization (1)](https://rheodata.com/en-us/blog/tag/snowflake-warehouse-optimization) - [Snowflake warehouse right-sizing (1)](https://rheodata.com/en-us/blog/tag/snowflake-warehouse-right-sizing) - [Token generation latency (1)](https://rheodata.com/en-us/blog/tag/token-generation-latency) - [VECTOR datatype Oracle (1)](https://rheodata.com/en-us/blog/tag/vector-datatype-oracle) - [VECTOR\_DISTANCE function (1)](https://rheodata.com/en-us/blog/tag/vector_distance-function) - [Vector embeddings Oracle (1)](https://rheodata.com/en-us/blog/tag/vector-embeddings-oracle) - [What's new GoldenGate 26ai (1)](https://rheodata.com/en-us/blog/tag/whats-new-goldengate-26ai) - [access control (1)](https://rheodata.com/en-us/blog/tag/access-control) - [activepass (1)](https://rheodata.com/en-us/blog/tag/activepass) - [adb (1)](https://rheodata.com/en-us/blog/tag/adb) - [add (1)](https://rheodata.com/en-us/blog/tag/add) - [add credentials (1)](https://rheodata.com/en-us/blog/tag/add-credentials) - [adminclient add credentials (1)](https://rheodata.com/en-us/blog/tag/adminclient-add-credentials) - [administration (1)](https://rheodata.com/en-us/blog/tag/administration) - [adw (1)](https://rheodata.com/en-us/blog/tag/adw) - [ai failures 2024 (1)](https://rheodata.com/en-us/blog/tag/ai-failures-2024) - [ai stratgies (1)](https://rheodata.com/en-us/blog/tag/ai-stratgies) - [ai-architecture (1)](https://rheodata.com/en-us/blog/tag/ai-architecture) - [all or nothing (1)](https://rheodata.com/en-us/blog/tag/all-or-nothing) - [allowPublicKeyRetrieval (1)](https://rheodata.com/en-us/blog/tag/allowpublickeyretrieval) - [alloydb (1)](https://rheodata.com/en-us/blog/tag/alloydb) - [alter extract 21c (1)](https://rheodata.com/en-us/blog/tag/alter-extract-21c) - [amazon (1)](https://rheodata.com/en-us/blog/tag/amazon) - [ansible (1)](https://rheodata.com/en-us/blog/tag/ansible) - [approximate-nearest-neighbor (1)](https://rheodata.com/en-us/blog/tag/approximate-nearest-neighbor) - [automl (1)](https://rheodata.com/en-us/blog/tag/automl) - [azure-cloud (1)](https://rheodata.com/en-us/blog/tag/azure-cloud) - [azure-native (1)](https://rheodata.com/en-us/blog/tag/azure-native) - [bastion (1)](https://rheodata.com/en-us/blog/tag/bastion) - [bastion host configuartion (1)](https://rheodata.com/en-us/blog/tag/bastion-host-configuartion) - [bastion setup oracle (1)](https://rheodata.com/en-us/blog/tag/bastion-setup-oracle) - [bug 30193036 (1)](https://rheodata.com/en-us/blog/tag/bug-30193036) - [bugs (1)](https://rheodata.com/en-us/blog/tag/bugs) - [build a compute node in oci (1)](https://rheodata.com/en-us/blog/tag/build-a-compute-node-in-oci) - [business-continuity (1)](https://rheodata.com/en-us/blog/tag/business-continuity) - [certificate-based authentication (1)](https://rheodata.com/en-us/blog/tag/certificate-based-authentication) - [change data capture (1)](https://rheodata.com/en-us/blog/tag/change-data-capture) - [changing ssh keys (1)](https://rheodata.com/en-us/blog/tag/changing-ssh-keys) - [channels (1)](https://rheodata.com/en-us/blog/tag/channels) - [cloud cost control (1)](https://rheodata.com/en-us/blog/tag/cloud-cost-control) - [cloud data platform cost control (1)](https://rheodata.com/en-us/blog/tag/cloud-data-platform-cost-control) - [cloud migration readiness assessment (1)](https://rheodata.com/en-us/blog/tag/cloud-migration-readiness-assessment) - [cloud-database-setup (1)](https://rheodata.com/en-us/blog/tag/cloud-database-setup) - [cloud-sql-migration (1)](https://rheodata.com/en-us/blog/tag/cloud-sql-migration) - [cloud-strategy (1)](https://rheodata.com/en-us/blog/tag/cloud-strategy) - [cohere command (1)](https://rheodata.com/en-us/blog/tag/cohere-command) - [compute (1)](https://rheodata.com/en-us/blog/tag/compute) - [compute portability (1)](https://rheodata.com/en-us/blog/tag/compute-portability) - [compute-instance (1)](https://rheodata.com/en-us/blog/tag/compute-instance) - [connect to database via bastion host (1)](https://rheodata.com/en-us/blog/tag/connect-to-database-via-bastion-host) - [connect to database via bastion host oci (1)](https://rheodata.com/en-us/blog/tag/connect-to-database-via-bastion-host-oci) - [consultants (1)](https://rheodata.com/en-us/blog/tag/consultants) - [content strategy (1)](https://rheodata.com/en-us/blog/tag/content-strategy) - [cost-optimization (1)](https://rheodata.com/en-us/blog/tag/cost-optimization) - [cryptographic authentication (1)](https://rheodata.com/en-us/blog/tag/cryptographic-authentication) - [curl (1)](https://rheodata.com/en-us/blog/tag/curl) - [daemon (1)](https://rheodata.com/en-us/blog/tag/daemon) - [data encryption (1)](https://rheodata.com/en-us/blog/tag/data-encryption) - [data fabric (1)](https://rheodata.com/en-us/blog/tag/data-fabric) - [data governance framework (1)](https://rheodata.com/en-us/blog/tag/data-governance-framework) - [data lake architecture (1)](https://rheodata.com/en-us/blog/tag/data-lake-architecture) - [data lakehouse platform (1)](https://rheodata.com/en-us/blog/tag/data-lakehouse-platform) - [data pipeline security (1)](https://rheodata.com/en-us/blog/tag/data-pipeline-security) - [data platform selection (1)](https://rheodata.com/en-us/blog/tag/data-platform-selection) - [data team workload management (1)](https://rheodata.com/en-us/blog/tag/data-team-workload-management) - [database AI transformation (1)](https://rheodata.com/en-us/blog/tag/database-ai-transformation) - [database administrators (1)](https://rheodata.com/en-us/blog/tag/database-administrators) - [database capacity planning tools (1)](https://rheodata.com/en-us/blog/tag/database-capacity-planning-tools) - [database certificate authentication (1)](https://rheodata.com/en-us/blog/tag/database-certificate-authentication) - [database compliance audit replication (1)](https://rheodata.com/en-us/blog/tag/database-compliance-audit-replication) - [database consolidation strategy (1)](https://rheodata.com/en-us/blog/tag/database-consolidation-strategy) - [database credential management (1)](https://rheodata.com/en-us/blog/tag/database-credential-management) - [database migration planning tools (1)](https://rheodata.com/en-us/blog/tag/database-migration-planning-tools) - [database modernization AI (1)](https://rheodata.com/en-us/blog/tag/database-modernization-ai) - [database replication management (1)](https://rheodata.com/en-us/blog/tag/database-replication-management) - [database transformation consulting (1)](https://rheodata.com/en-us/blog/tag/database-transformation-consulting) - [database-failover (1)](https://rheodata.com/en-us/blog/tag/database-failover) - [database-vectors (1)](https://rheodata.com/en-us/blog/tag/database-vectors) - [db\_owner risk SQL Server replication (1)](https://rheodata.com/en-us/blog/tag/db_owner-risk-sql-server-replication) - [dba\_capture (1)](https://rheodata.com/en-us/blog/tag/dba_capture) - [dba\_queues (1)](https://rheodata.com/en-us/blog/tag/dba_queues) - [dbms\_aqadm.drop\_queue\_table (1)](https://rheodata.com/en-us/blog/tag/dbms_aqadm-drop_queue_table) - [dbms\_comparison (1)](https://rheodata.com/en-us/blog/tag/dbms_comparison) - [ddl (1)](https://rheodata.com/en-us/blog/tag/ddl) - [direct initial load (1)](https://rheodata.com/en-us/blog/tag/direct-initial-load) - [dml (1)](https://rheodata.com/en-us/blog/tag/dml) - [docker goldengate (1)](https://rheodata.com/en-us/blog/tag/docker-goldengate) - [docker images (1)](https://rheodata.com/en-us/blog/tag/docker-images) - [dynamic (1)](https://rheodata.com/en-us/blog/tag/dynamic) - [edb database (1)](https://rheodata.com/en-us/blog/tag/edb-database) - [elephant database (1)](https://rheodata.com/en-us/blog/tag/elephant-database) - [eliminate database password authentication (1)](https://rheodata.com/en-us/blog/tag/eliminate-database-password-authentication) - [emd360 (1)](https://rheodata.com/en-us/blog/tag/emd360) - [enable ddl (1)](https://rheodata.com/en-us/blog/tag/enable-ddl) - [enterprise (1)](https://rheodata.com/en-us/blog/tag/enterprise) - [enterprise AI (1)](https://rheodata.com/en-us/blog/tag/enterprise-ai) - [enterprise AI implementation (1)](https://rheodata.com/en-us/blog/tag/enterprise-ai-implementation) - [enterprise AI infrastructure (1)](https://rheodata.com/en-us/blog/tag/enterprise-ai-infrastructure) - [enterprise data governance (1)](https://rheodata.com/en-us/blog/tag/enterprise-data-governance) - [enterprise data integration (1)](https://rheodata.com/en-us/blog/tag/enterprise-data-integration) - [enterprise data strategy (1)](https://rheodata.com/en-us/blog/tag/enterprise-data-strategy) - [enterprise goldengate backup solution (1)](https://rheodata.com/en-us/blog/tag/enterprise-goldengate-backup-solution) - [enterprise manager (1)](https://rheodata.com/en-us/blog/tag/enterprise-manager) - [exception handling (1)](https://rheodata.com/en-us/blog/tag/exception-handling) - [experts in oracle goldengate (1)](https://rheodata.com/en-us/blog/tag/experts-in-oracle-goldengate) - [extract changes (1)](https://rheodata.com/en-us/blog/tag/extract-changes) - [extract load transform (1)](https://rheodata.com/en-us/blog/tag/extract-load-transform) - [extract transform load (1)](https://rheodata.com/en-us/blog/tag/extract-transform-load) - [failures (1)](https://rheodata.com/en-us/blog/tag/failures) - [fintech postgreSQL (1)](https://rheodata.com/en-us/blog/tag/fintech-postgresql) - [firewalld goldengate (1)](https://rheodata.com/en-us/blog/tag/firewalld-goldengate) - [firewalld microservices (1)](https://rheodata.com/en-us/blog/tag/firewalld-microservices) - [fivetran (1)](https://rheodata.com/en-us/blog/tag/fivetran) - [framework (1)](https://rheodata.com/en-us/blog/tag/framework) - [frameworks (1)](https://rheodata.com/en-us/blog/tag/frameworks) - [free tools (1)](https://rheodata.com/en-us/blog/tag/free-tools) - [fresh data (1)](https://rheodata.com/en-us/blog/tag/fresh-data) - [gemini (1)](https://rheodata.com/en-us/blog/tag/gemini) - [genai (1)](https://rheodata.com/en-us/blog/tag/genai) - [general information (1)](https://rheodata.com/en-us/blog/tag/general-information) - [ggsci (1)](https://rheodata.com/en-us/blog/tag/ggsci) - [ggsmon (1)](https://rheodata.com/en-us/blog/tag/ggsmon) - [goldengate active passive (1)](https://rheodata.com/en-us/blog/tag/goldengate-active-passive) - [goldengate backup automation (1)](https://rheodata.com/en-us/blog/tag/goldengate-backup-automation) - [goldengate bug (1)](https://rheodata.com/en-us/blog/tag/goldengate-bug) - [goldengate errors (1)](https://rheodata.com/en-us/blog/tag/goldengate-errors) - [goldengate experts (1)](https://rheodata.com/en-us/blog/tag/goldengate-experts) - [goldengate free (1)](https://rheodata.com/en-us/blog/tag/goldengate-free) - [goldengate github integration (1)](https://rheodata.com/en-us/blog/tag/goldengate-github-integration) - [goldengate high availiability (1)](https://rheodata.com/en-us/blog/tag/goldengate-high-availiability) - [goldengate maa (1)](https://rheodata.com/en-us/blog/tag/goldengate-maa) - [goldengate microservices port (1)](https://rheodata.com/en-us/blog/tag/goldengate-microservices-port) - [goldengate microservices ports (1)](https://rheodata.com/en-us/blog/tag/goldengate-microservices-ports) - [goldengate ogg-02028 (1)](https://rheodata.com/en-us/blog/tag/goldengate-ogg-02028) - [goldengate parameter file backup (1)](https://rheodata.com/en-us/blog/tag/goldengate-parameter-file-backup) - [google cloudsql (1)](https://rheodata.com/en-us/blog/tag/google-cloudsql) - [google mysql migration (1)](https://rheodata.com/en-us/blog/tag/google-mysql-migration) - [heatwave experts (1)](https://rheodata.com/en-us/blog/tag/heatwave-experts) - [high performance mysql (1)](https://rheodata.com/en-us/blog/tag/high-performance-mysql) - [human creativity AI (1)](https://rheodata.com/en-us/blog/tag/human-creativity-ai) - [human vs AI writing (1)](https://rheodata.com/en-us/blog/tag/human-vs-ai-writing) - [hybrid cloud data architecture (1)](https://rheodata.com/en-us/blog/tag/hybrid-cloud-data-architecture) - [integrated extract oracle (1)](https://rheodata.com/en-us/blog/tag/integrated-extract-oracle) - [integrated replicat oracle (1)](https://rheodata.com/en-us/blog/tag/integrated-replicat-oracle) - [lic (1)](https://rheodata.com/en-us/blog/tag/lic) - [license (1)](https://rheodata.com/en-us/blog/tag/license) - [logmnr\_session$ (1)](https://rheodata.com/en-us/blog/tag/logmnr_session) - [managed service provider (1)](https://rheodata.com/en-us/blog/tag/managed-service-provider) - [managed services for database teams (1)](https://rheodata.com/en-us/blog/tag/managed-services-for-database-teams) - [management (1)](https://rheodata.com/en-us/blog/tag/management) - [migration compatibility validation (1)](https://rheodata.com/en-us/blog/tag/migration-compatibility-validation) - [monitor oracle goldengate rest api (1)](https://rheodata.com/en-us/blog/tag/monitor-oracle-goldengate-rest-api) - [monolithic database architecture (1)](https://rheodata.com/en-us/blog/tag/monolithic-database-architecture) - [move off of oracle (1)](https://rheodata.com/en-us/blog/tag/move-off-of-oracle) - [multi-cloud data platform (1)](https://rheodata.com/en-us/blog/tag/multi-cloud-data-platform) - [oci bastion (1)](https://rheodata.com/en-us/blog/tag/oci-bastion) - [oem emd360 (1)](https://rheodata.com/en-us/blog/tag/oem-emd360) - [ogg deployments (1)](https://rheodata.com/en-us/blog/tag/ogg-deployments) - [open table format (1)](https://rheodata.com/en-us/blog/tag/open-table-format) - [oracle database (1)](https://rheodata.com/en-us/blog/tag/oracle-database) - [preventing tech employee attrition (1)](https://rheodata.com/en-us/blog/tag/preventing-tech-employee-attrition) - [reducing on-call burnout (1)](https://rheodata.com/en-us/blog/tag/reducing-on-call-burnout) - [securing Oracle GoldenGate on SQL Server (1)](https://rheodata.com/en-us/blog/tag/securing-oracle-goldengate-on-sql-server) - [tech team burnout (1)](https://rheodata.com/en-us/blog/tag/tech-team-burnout) - [thought leadership (1)](https://rheodata.com/en-us/blog/tag/thought-leadership) - [vector database consolidation (1)](https://rheodata.com/en-us/blog/tag/vector-database-consolidation) See all - - [1](https://rheodata.com/en-us/blog) - [2](https://rheodata.com/en-us/blog/tag/21c/page/2) - ##### About RheoData RheoData is based out of Metro Atlanta, GA and provide expert Oracle, Microsoft, Google, and Snowflake services.  Let us  know how we can help! ##### Links - [About Us](https://rheodata.com/who-we-are) - [FrostCore](https://rheodata.com/frostcore) - [RedCore](https://rheodata.com/redcore) - [BlueCore](https://rheodata.com/bluecore) ##### Contact us [hello@rheodata.com](mailto:hello@rheodata.com) ©RheoData2026. All Rights Reserved. ```json { "@context" : "https://schema.org", "@type" : "Organization", "address" : { "@type" : "PostalAddress", "addressCountry" : "US", "addressRegion" : "GA" }, "description" : "Elite specialist partner for Oracle, Snowflake, BigQuery, and AI-ready data platforms.", "email" : "hello@rheodata.com", "foundingDate" : "2020", "logo" : "https://rheodata.com/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png", "name" : "RheoData", "sameAs" : [ "https://www.linkedin.com/company/rheodata" ], "url" : "https://rheodata.com" } ``` ```json { "@context" : "https://schema.org", "@type" : "WebSite", "name" : "RheoData", "potentialAction" : { "@type" : "SearchAction", "query-input" : "required name=search_term_string", "target" : "https://rheodata.com/search?q={search_term_string}" }, "url" : "https://rheodata.com" } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "", "url" : "" }, "dateModified" : "2026-04-17T17:31:04+0000", "datePublished" : "2025-10-30T17:41:53+0000", "description" : "21c | RheoData Blog Posts", "headline" : "<span id="hs_cos_wrapper_name" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="text" >rheodata_blog listing page</span>", "image" : "", "mainEntityOfPage" : { "@id" : "https://rheodata.com/en-us/blog/tag/21c", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://rheodata.com/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "With any type of replication configuration or replication tool, primary purpose is to move the data as transactions are committed between databases. Any of the tools on the market are great for replicating data, but where replication starts to become interesting is when the metadata for tables needs to be replicated. When something changes at the data definition layer occur, these changes have be shipped across the network. Replication tools need to be able to handle the capture, shipping, and applying of an object’s data definition language (DDL). With Oracle GoldenGate, improvements have occurred over the years to make replicating DDL easier. Although, replicating DDLs have become easier there are items that need to be considered. In this post, we’ll look at these common items. Overview of DDL Synchronization Oracle GoldenGate supports the synchronization of DDL operations from one database to another. DDL synchronization can be active when: Business applications are actively accessing and updating the source and target objects Oracle GoldenGate transactional data synchronization is active (DML) The components that support the replication of DDL and replication of transactional data changes (DML) are independent of each other. Therefore, you can synchronize: Just DDL changes Just DML changes Both DML and DDL This means that Oracle GoldenGate can perform both DML and DDL at the same time or independent of each other. This provides flexibility to the overall architecture and allows the administrators the option to define what needs to be replicated and when. Fetch-Related Inconsistencies With everything being flexible and easy to replicate, there is a defined process to ensure that inconsistencies are minimized when DML and DDL are fetched. For example, the following process will help prevent fetch-related inconsistencies while Oracle table columns are being modified: Pause all DML on table (i.e. stop any process that is processing inserts, update, or deletes) Wait for the Extract to finish capturing all remaining redo; wait for Replicat to finish processing all captured data in trail. Execute the DDL on source; confirm DDL changes on target Resume source DML on table Enabling DDL Replication DDL is useful in dynamic environments which change constantly. By default, the status of DDL replication supports the following: On source (Extract), the Oracle GoldenGate DDL support is disabled by default. Must be configured with the DDL parameter. On target (Replicat), DDL support is enabled by default, to maintain the integrity of transactional data that is replicated. DDL Parameter (Extract/Replicat) The DDL parameter can be used in both the Extract and Replicat parameter files. By using DDL parameter in the Extract is will enable DDL capture. It can be omitted from the Replicat parameter since DDL is enabled on the target side by default. Sample Parameter Files Extract: extract EXT useridalias SOURCE domain OracleGoldenGate exttrail aa ddl sourcecatalog chip table tstusr.random_lrg_; Replicat: replicat REP useridalias PDBSOURCE domain OracleGoldenGate ddl map chip.tstusr.random_lrg_, target chip.tstusr1.random_lrg; Hopefully, this quick post shows you how easy it is to get DDL enabled within Oracle GoldenGate. Enjoy!!", "author" : { "@type" : "Person", "name" : "Fame", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/fame" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Basic DDL Replication with Oracle GoldenGate", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Ansible has become a standard configuration tool for many enterprises and is used is many CI/CD pipelines to build standard implementations with the organizations. Ansible is a very powerful tool that leveraged secure shell (ssh) to make connect to target hosts and push to the modules needed to build the platform. Like any tool, Ansible is very flexible and lends itself to the usage of the user. Software packages like Oracle Database and Oracle GoldenGate can be baked into playbooks providing a standard installation process. With the latest release of Oracle GoldenGate 21c, RheoData has built a standard template that allows its consultants to quickly build Oracle GoldenGate 21c into any environment. This blog post, we will look at the playbook and see how Oracle GoldenGate 21c is installed on a Linux host. Variable File The first thing that has to be defined is the variables that are going to be used within playbook. There are different ways of defining variables, but for simplify we used the sub-folder structure (defaults) which house the file main.yml. Within this main.yml file, all variables needed are defined. Below is the current consturct of our variables file: stage_dir: /opt/software/ stage_ogg: /opt/software/ogg19cma oracle_base: /opt/app/oracle oracle_inventory: /opt/app/oraInventory oracle_home_client: /opt/app/oracle/product/client ogg_home: /opt/app/oracle/product/19.1.0/oggcore_21c ogg_deployment_home: /opt/app/oracle/gg_deployment ora_group: oinstall oracle_user: oracle root_user: root ggsoft19c_rsp: oggcore_21c.rsp installation: Oracle GoldenGate zip_files: /Users/bocurtis/Build_Software/zip_files/ response_files: /Users/bocurtis/Build_Software/response_files/ script_files: /Users/bocurtis/Build_Software/scripts/ oracle_client_lite_19c: instantclient-basiclite-linux.x64-19.5.0.0.0dbru.zip oracle_client_lite_18c: instantclient-basiclite-linux.x64-18.5.0.0.0dbru.zip oracle_client_12c: instantclient-basic-linux.x64-12.2.0.1.0.zip gg_services_software: 213000_fbo_ggs_Linux_x64_services_shiphome.zip set_passwords: set_passwd.sh self_sign: ggSelfSignCerts.py nginx_setup: configureNginx.sh sm_start: startServiceManager.sh sm_stop: stopServiceManager.sh As you review the list of variables that are needed for installing Oracle GoldenGate 21c (above), notice that some of these variables reference scripts that can be used to make managing Oracle GoldenGate 21c a bit easier. These scripts do not come with Oracle GoldenGate 21c. Tasks With the variables defined, the next thing to do is define the tasks that must be done in order to install Oracle GoldenGate 21c. Just like the variables file, the tasks are provided in a sub-folder structure (tasks). Within this folder, we only needed another main.yml file, but for step purposes we broke the tasks down further. With the current tasks, we have a main.yml, copy.yml, and install.yml. These three file cover all the steps needed to install Oracle GoldenGate 21c within a single host. Lets take a look at these now: main.yml The main.yml file for Tasks, is the main file that will drive all of the installation. This file uses all variables that was defined earlier. --- - name: Display Pre-Install Message remote_user: become: yes debug: msg: - ' Installation started at :' - name: Update RPM Packages remote_user: become: yes yum: name: * state: latest - name: Install Oracle Pre-Requistes remote_user: become: yes yum: name: oracle-database-preinstall-19c state: latest - name: Create required directories remote_user: become: yes file: path={{item}} state=directory owner= group= mode=0755 with_items: - - - - - - - - tags: - ogg19c_directories - name: tasks/copy.yaml instead of 'main' import_role: name: gg19cSetup tasks_from: copy - name: tasks/install.yaml instead of 'main' import_role: name: gg19cSetup tasks_from: install - name: Display Post-Install Message remote_user: become: yes debug: msg: - ' Installation finished at :' ... copy.yml The copy task is called from the main.yml file and used to copy the needed binaries and files to the target host. At the same time set the permissions needed on these files. --- - name: Coping required files remote_user: become: yes copy: src: {{item}} dest: owner: group: mode: 0555 with_items: - - - - - - - - - - ... install.yml The install task is called from the main.yml file and begins to perform the install Oracle GoldenGate 21c. The task does everything from unzipping the Oracle Client libraries and Oracle GoldenGate 21c, through configuring the .bashrc environment. --- - name: Unzipping/Installing Oracle Database Client 19c remote_user: become: yes become_user: unarchive: src: dest: extra_opts: - --j remote_src: true - name: Unzipping/Installing Oracle Database Client 18c remote_user: become: yes become_user: unarchive: src: dest: extra_opts: - --j remote_src: true - name: Unzipping Oracle GoldenGate 21c remote_user: become: yes become_user: unarchive: src: dest: remote_src: true - name: Installing Oracle GoldenGate 21c for Oracle Database 21c remote_user: become: yes become_user: shell: cmd: /fbo_ggs_Linux_x64_services_shiphome/Disk1/runInstaller -silent -showProgress -ignoreSysPrereqs -waitForCompletion -responseFile >> /tmp/ggInstall.log ignore_errors: true - name: Running root script remote_user: become: yes shell: cmd: /opt/app/oraInventory/orainstRoot.sh >> /tmp/ggInstall.log - name: Setting Passwords remote_user: become: yes shell: cmd: - name: Setting .bashrc remote_user: become: yes blockinfile: dest: /home/oracle/.bashrc block: | export OGG_HOME= export ORACLE_HOME= export ORACLE_BASE= export LD_LIBRARY_PATH=/lib export PATH=$OGG_HOME/bin:$LD_LIBRARY_PATH:$PATH insertbefore: BOF create: yes backup: no ... Once the playbook is done, a fully functioning Oracle GoldenGate 21 environment is installed and ready to use. Aft this point, other Oracle GoldenGate 21c components can be created using either the command line (AdminClient), the HTML pages, or REST api. Summary Through this post, we were showing you how you can use Ansible to install Oracle GoldenGate 21c. Using this process, Oracle GoldenGate 21c can be installed on any platform in an automated fashion.", "author" : { "@type" : "Person", "name" : "Fame", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/fame" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Deploying Oracle GoldenGate 21c with Ansible", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/deploying-oracle-goldengate-21c-with-ansible", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number for access. For the first run of the Oracle GoldenGate Configuration Assistant (OGGCA), the assistant will create the ServiceManager (1 port) and the first deployment (5 ports). That means six ports would need to be opened on a firewall to run a single Oracle GoldenGate (Microservices) deployment. This only increases by five ports for each deployment built under a single ServiceManager. To address this, an open-source solution called NGINX allows all the ports within the deployment to be consolidated to a single port. The single port that can be used with NGINX is either 80 (HTTP) or 443 (HTTPS); which will enable Oracle GoldenGate (Microservices) to be used over a standard firewall port Downloading Binaries The NGINX binaries need to be downloaded regardless of where you install Oracle GoldenGate (Microservices). For Oracle Enterprise Linux, I documented the process here. When you start to expand the installation base for Microservices, the installation of NGINX becomes similar yet different. To install NGINX on an RedHat Linux 7.2 , the following steps should be followed. 1. SSH into the RedHat instance $ ssh @ 2. Sudo to Root $ sudo su – 3. Install and Confirm installation $ yum -y install nginx && yum list install nginx After installing the NGINX the next thing that must be done is to configure it against the Oracle GoldenGate (Microservices) environment. Configure NGINX Oracle has made it easy for Oracle GoldenGate administrators to configure the NGINX interface after the installation. They provided a script called “ReverseProxySettings” in the $OGG_HOME/lib/utl directory. This script is used to build the Nginx configuration file based on the deployments running on the AWS EC2 node. The steps to configure the reverse proxy are as follows: 1. Change to the Reverse Proxy directory under $OGG_HOME $ cd $OGG_HOME/lib/utl/reverseproxy 2. Run ReverseProxySettings with options (unsecure access) $ ./ReverseProxySettings -u oggadmin -P -o ogg.conf http://localhost: 3. Copy the config file to the NGINX directory $ sudo cp ogg.conf /etc/nginx/conf.d/nginx.conf 4. Create a dummy cert $ sudo sh /etc/ssl/certs/make-dummy-cert /etc/nginx/ogg.pem 5. Start NGINX $ sudo nginx & 6. Test/validate NGINX config $ sudo nginx -t 7. Reload NGINX $ sudo nginx -s reload 8. Access the ServiceManager and other services without port numbers Note: The ogg.pem must be downloaded and uploaded to your local cert wallet to access via a web browser. End Result Once everything with the NGINX is configured, Oracle GoldenGate (Microservices) can be accessed by URL using the standard port of 80 (HTTP) or 443 (HTTPS). This enables Oracle GoldenGate (Microservices) environments to be accessed over standard firewall rules.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Configuring Nginx on RedHat Linux 7.9 for Oracle GoldenGate 21c", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/nginx-url-noport-Oct-31-2025-04-51-57-0433-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c-2", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "A quick post as a reminder for myself some time down the road. After all, we all need reminders every once in a while! Prior to Oracle Database 12c finding a list of default users within the database was always a pain. In Oracle Database 12c or later, this has become much simpler. Oracle introduced a column on the *_users views that allows the end users to identify what users are maintained by Oracle. This column name is ORACLE_MAINTAINED. The value of the column is either “N” or “Y”. If it is “Y”, then user account is maintained by Oracle. A simple query of the ALL_USERS view will return about 57 different accounts that are maintained by Oracle in Oracle Database 19c (Autonomous Data Warehouse). select * from all_users where oracle_maintained = 'Y' order by username; For more information, the Oracle Database 19c docs can be referenced here.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Identifying Predefined Administrative Accounts in Autonomous Database or any other Oracle database", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/identify_predefined_accounts-1024x638-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "After installing Oracle GoldenGate with a manual ServiceManager, you realize that the ServiceManager will not come back up on a reboot. Although this can be annoying, Oracle GoldenGate is doing what it was asked to. Additionally, after the ServiceManager has been configured, there is no way to convert the ServiceManager to daemon process, unless they whole deployment is rebuilt. I came up with a way to start Oracle GoldenGate’s ServiceManager through using the Linux SystemCTL process. By using systemctl, a manual ServiceManager can be turned into a rebootable service. Let’s look at how this is done. Shell Script The first thing that needs to be done is to produce a shell script that will call the startSM.sh script. The startSM.sh script is provide by Oracle to start the ServiceManager, but there are a few environment variables that must be set before it can be ran. By writing a wrapper script to call the startSM.sh script, all that can be done in a single pass. The contents of the script is as follows: File 1: startServiceManager.sh #!/bin/bash # Copyright (c) 2020 RheoData, LLC and/or its affiliates. All rights reserved. # # Since: March 2019 # Author: bobby@rheodata.com # Description: Start ServiceManager # # DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER. # export OGG_HOME=/opt/app/oracle/product/21.3.0/oggcore_21c export DEPLOYMENT_HOME=/opt/app/oracle/gg_deployments/ServiceManager export OGG_ETC_HOME=/opt/app/oracle/gg_deployments/ServiceManager/etc export OGG_VAR_HOME=/opt/app/oracle/gg_deployments/ServiceManager/var echo Starting ServiceManager $DEPLOYMENT_HOME/bin/startSM.sh echo Done By looking at the startServiceManager.sh script, it clearly pointed out that the $OGG_HOME, $DEPLOYMENT_HOME, $OGG_ETC_HOME, and $OGG_VAR_HOME are defined. These are the environment variables that are needed to bring up the ServiceManager. Service File The next thing that needs to be configured is the service file. This file is used by systemd process to interact with the service. This file is broken down into three parts – Unit, Service, Install. The Unit section holds the description and other items that describe the service. The Service section is where we define the type, user, group and the shell script that will be executed. In this case, we are calling startServiceManage.sh. File 2: ServiceManager.service [Unit] Description=Oracle GoldenGate 21c ServiceManager Control [Service] Type=forking User=oracle Group=oinstall ExecStart=/bin/bash /home/oracle/scripts/startServiceManager.sh [Install] WantedBy=multi-user.target Once this file is create, it needs to be save to /etc/systemd/system directory. This is the default location for all the services that are running on RHEL/OEL. Create the Service With the shell script and services file create, now is the time to create the service itself. This process is straight forward. $sudo su – $systemctl daemon-reload $systemctl enable ServiceManager.service Since this is a new service that is being created, the daemons must be reloaded. This pulls in the ServiceManager.service file to the systemd process. Then the enable call will create a symbolic link between the ServiceManager.service file in /etc/systemd/system/multi-user.target.wants and the same file in /etc/system/system. After the service is enabled, we can force the ServiceManager down by simply killing the process. Don’t worry any associated deployments services and extract/replicat process will stay running. With the ServiceManager down, start it back up with the new services; with: $sudo su – $systemctl start ServiceManager Check the Service If everything is working, the ServiceManager will be brought up and accessible. The status of the ServiceManager can then be checked using the status option of systemctl. $sudo su – $systemctl status ServiceManager $ systemctl status ServiceManager ● ServiceManager.service - Oracle GoldenGate 21c ServiceManager Control Loaded: loaded (/etc/systemd/system/ServiceManager.service; enabled; vendor preset: disabled) Active: active (running) since Tue 2023-01-31 17:21:34 GMT; 3h 15min ago Main PID: 22414 (ServiceManager) CGroup: /system.slice/ServiceManager.service └─22414 /opt/app/oracle/product/21.3.0/oggcore_21c/bin/ServiceManager –quiet This is how you convert a manual start ServiceManager into a ServiceManager that will be started on reboot.", "author" : { "@type" : "Person", "name" : "rheostage5132", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/rheostage5132" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Configure Oracle GoldenGate’s ServiceManager as a Linux Service", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/rd_configure_sm_service-1024x553-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number for access. For the first run of the Oracle GoldenGate Configuration Assistant (OGGCA), the assistant will create the ServiceManager (1 port) and the first deployment (5 ports). That means six ports would need to be opened on a firewall to run a single Oracle GoldenGate (Microservices) deployment. This only increases by five ports for each deployment built under a single ServiceManager. To address this, an open-source solution called NGINX allows all the ports within the deployment to be consolidated to a single port. The single port that can be used with NGINX is either 80 (HTTP) or 443 (HTTPS); which will enable Oracle GoldenGate (Microservices) to be used over a standard firewall port Downloading Binaries The NGINX binaries need to be downloaded regardless of where you install Oracle GoldenGate (Microservices). For Oracle Enterprise Linux, I documented the process here. When you start to expand the installation base for Microservices, the installation of NGINX becomes similar yet different. To install NGINX on an Amazon Web Services (AWS) EC2 instance, the following steps should be followed. For more details, you can also reference this blog post on installing Nginx -> here or here. 1. SSH into the AWS EC2 instance $ ssh -I ~/.ssh/rd-usf-tst.pem ec2-user@ 2. Sudo to Root $ sudo su – 3. Use Amazon Extras to install NGINX $ amazon-linux-extras install nginx1.12 4. Confirm installation $ yum list install nginx After installing the NGINX on the AWS EC2 instance, the next thing that must be done is to configure it against the Oracle GoldenGate (Microservices) environment. Configure NGINX Oracle has made it easy for Oracle GoldenGate administrators to configure the NGINX interface after the installation. They provided a script called “ReverseProxySettings” in the $OGG_HOME/lib/utl directory. This script is used to build the Nginx configuration file based on the deployments running on the AWS EC2 node. The steps to configure the reverse proxy are as follows: 1. Change to the Reverse Proxy directory under $OGG_HOME $ cd $OGG_HOME/lib/utl/reverseproxy 2. Run ReverseProxySettings with options (unsecure access) $ ./ReverseProxySettings -u oggadmin -P -o ogg.conf http://localhost: 3. Copy the config file to the NGINX directory $ sudo cp ogg.conf /etc/nginx/conf.d/nginx.conf 4. Create a dummy cert $ sudo sh /etc/ssl/certs/make-dummy-cert /etc/nginx/ogg.pem 5. Start NGINX $ sudo nginx & 6. Test/validate NGINX config $ sudo nginx -t 7. Reload NGINX $ sudo nginx -s reload 8. Access the ServiceManager and other services without port numbers Note: The ogg.pem must be downloaded and uploaded to your local cert wallet to access via a web browser. End Result Once everything with the NGINX is configured, Oracle GoldenGate (Microservices) can be accessed by URL using the standard port of 80 (HTTP) or 443 (HTTPS). This enables Oracle GoldenGate (Microservices) environments to be accessed over standard firewall rules.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Configuring Nginx on AWS EC2 for Oracle GoldenGate 21c", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/nginx-url-noport-1-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "News on the Oracle GoldenGate front!!!!! Over the years, Oracle has taken the Oracle GoldenGate product and have used it for a wide range of use-cases. In 2017, Oracle introduced the world to the next evolution of Oracle GoldenGate with the release of Oracle GoldenGate Microservices in the 12.3.0.1 version. At the time, I had the privilege of shepherding in the this new architecture and truly believe it is moving the right direction for high-volume replication, hub-n-spokes architectures, and data mesh frameworks. At the same time, what I was witnessing and was a bit concern about is the close integration between the Oracle database and the Oracle GoldenGate product. Back in 2013, I wrote about Advanced Replication and Streams being dead due to Oracle Database documentation mentioning that the direction for replication was changing towards Oracle GoldenGate. Fast forward a few years … when I woke up this morning and scrolling through LinkedIn, some associates were posting information on Oracle Database 21c New Features. And the transition to full Oracle Database integration has begun …. In the new features doc for Oracle Database 21c, Oracle GoldenGate can be found under “Performance and High Availability”. Under this category, there are features related to the following: Automatic CDR Enhancements Improved Support for Table Replication for Oracle GoldenGate LogMiner Views Added to Assist Replication Oracle GoldenGate for Oracle and Stream Support for JSON Data Type These features are only the start of what should be seen as the Oracle GoldenGate product becomes more and more integrated into the Oracle Database. The real questions is going to be around the heterogenous nature of Oracle GoldenGate. With the integration of the Oracle side of the product moving into the Oracle Database, will Oracle GoldenGate eventually drop the heterogenous functionality of the product? I don’t think so … that would be contradictory to their marketing of a “data mesh” framework and pushing customers into that model. What I would expect to see is more of the microservices architecture coming to the heterogenous platforms and even Big Data. This would align beautifully with the “data mesh” marketing and allow for a single point of reference with multiple product offerings. Oracle is moving the Oracle GoldenGate product to be closer related with the Oracle Database and keeping the heterogenous nature of the product. Only time will tell if merging into the Oracle database is going to benefit the product and Oracle. Just my 2 cents… Enjoy!!!", "author" : { "@type" : "Person", "name" : "rheostage5132", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/rheostage5132" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "The transition has begun … Oracle GoldenGate merging into Oracle Database 21 (new features)", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/the-transition-has-begun-oracle-goldengate-merging-into-oracle-database-21-new-features", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Does data drive your organization? Have you started your transition to a Modern Data Platform? Does your organization understand what it means or takes to transition to a Modern Data Platform? Yes, these are questions that organizations think they know the answer to until they start the transition and bills from cloud providers come in. All concerns that RheoData can help organizations solve from Day 1 and help maintain on Day 2 through our service offerings. At the same time, a solid understanding of what a data drive platform consists of is key. Without expertise in Oracle Cloud Infrastructure (OCI) and data integration, we find it essential for organizations to understand and define their goals related to Modern Data Platforms. For the better part of a decade, the cloud has brought about many changes that organizations have to evaluate, review, and use data daily. One of these changes is acknowledging that the modern data architecture’s idea of one-size-fits-all eventually leads to compromises. It is not simply about integrating a data lake with a data warehouse, but rather a data lake, data warehouse, and purpose-built data stores, enabling a unified governance approach and simplified data movement. In approaching the modern data architecture on OCI, Oracle – the leader in databases with Oracle Database and MySQL (open-source), customers can rapidly build scalable data lakes, use a broad and deep collection of purpose-built data services, ensure compliance via a unified data access, security, and governance, scale their systems at a low cost without compromising performance, and easily share data across organizational boundaries, allowing them to make decisions with speed and agility at scale. Why you need a modern data platform Data volumes are increasing alarmingly and are projected to reach or surpass 180 zettabytes by 2025 (less than two years away). Traditional on-premises data ingestion and analytics approaches can’t handle these data volumes because they don’t scale well enough and are too expensive to build and maintain. Many organizations are taking all their data from various silos and aggregating all that data in one location, what many call a data lake, to do analytics and ML directly on top of that data. The same organizations are storing or offloading other data into purpose-built data stores to analyze and generate insights from structured and unstructured data, leaving organizations with data distributed across the enterprise and possibly unavailable to the broader organization. Through a Modern Data Platform, data ingestion and data analytics are governed, secure, and performance-driven to provide meaningful business insight, real-time visibility, and accurate forecasting or predictions. Why choose Oracle’s Modern Data Platform Oracle offers the most complete, open, and intelligent modern data platform. These three pillars of Oracle’s modern data platform make a compelling argument for Oracle Cloud Infrastructure (OCI) and why organizations should leverage their existing investments in Oracle technologies or take another look at the only cloud built for enterprises: Complete: Oracle’s Modern Data Platform is designed with you in mind, offering, and providing a unique suite of services for the whole data stack Open: Empowers organizations with flexible workload deployment, seamless integration, and open solutions. Meeting you where you are. Intelligent: Benefits from the latest artificial intelligence innovations to surface insights directly inside the apps that support your critical business functions. Enriching data through embedded intelligence. Image 1: Oracle’s Modern Data Platform Related Data Platform Products Oracle’s background in databases and data management over the last forty years has provided Oracle with industry-tested products that have transitioned to Oracle Cloud Infrastructure (OCI) and the Modern Data Platform. These products enable organizations to build out their modern data platforms quickly and with a known knowledge base. Get started with Oracle Modern Data Platform Oracle provides many options to get started on your Modern Data Platform journey. Use the links below to check out how Oracle Cloud Infrastructure (OCI) can be used to modernize your data platform! Free OCI Services (here) Learn with Step-by-Step guidance (here) Explore over 150 reference architectures (here) Estimate your costs (here) Contact RheoData to get started (here) today! Contact Info Give RheoData a call today to start architecting your Modern Data Platform.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Modern Data Platform with Oracle Cloud Infrastructure (OCI)", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/moderdataplatform-oci-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/moder-data-platform", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "A data pipeline is a method in which raw data or unchanged data is ingested from various data sources and shipped to another data store, like a relational database, data lake, or a data warehouse; where the data is eventually used for analysis. Before data is eventually used it undergoes some form of data processing or transformation; including filtering, masking, and aggregations. The transformation process ensures data integration and standardization. This is particularly important when the destination for the raw data is a relational database. As the names suggests, data pipelines act as the “piping” or “plumbing” for many different projects in modern data platforms, data science projects, or business intelligence dashboards. Data is can be and often sourced through a wide variety of places – APIs, SQL, NoSQL, flat files, etc., but the data is not ready for immediate use. Preparation of data usually falls on the shoulders of data engineers or data scientist, who structure the data to meet the need of the business and the associated use cases. The type of data processing that a data pipeline requires is usually determined through a mix of exploratory data analysis and defined business requirements. Once the data has been appropriately filtered, merged, and summarized, it can then be stored and used. Well-organized data pipelines provide the foundation for a range of data projects; this can include exploratory data analyses, data visualizations, and machine learning tasks. Types of Pipelines There are a few different types of data pipelines, but two primary types stand out; which are batch processing and stream processing. Batch Processing The development of batch processing was critical step in building data infrastructures that were reliable and scalable in the early days. This type of processing enabled organizations to move and process large amounts of data into repositories at set time intervals, typically during off-peak hours. This way workloads were not impacted as batch processing jobs tend to work with large volumes of data; taxing the overall system. Batch processing is the optimal data pipleline when there isn’t a immediate need to analyze a specific dataset and is more associated with the Extract, Transform, and Load (ETL) data ingestion process. Streaming Data Streaming data is leveraged when it is required for data to be continuously updated. For example, apps or point of sale (POS) systems need real-time data to update inventory and sales history of their products; that way, sellers can inform consumers if a product is in stock or not. A single action, like a product sale, is considered an “event”, and related events, such as adding an item to checkout, are typically grouped together as a “topic” or “stream.” These events are then transported via messaging systems or message brokers, such as the open-source offering, Apache Kafka. Since data events are processed shortly after occurring, streaming processing systems have lower latency than batch systems, but aren’t considered as reliable as batch processing systems as messages can be unintentionally dropped or spend a long time in queue. Message brokers help to address this concern through acknowledgements, where a consumer confirms processing of the message to the broker to remove it from the queue. Architecture of Data Pipelines There are three phases that make of a data pipeline. Data Ingestion Data Transformation Data Storage Within these three phases, data is moved and transformed as needed to ensure data can be used by an organization. Data Ingestion: Data is collected from various data sources, including various data structures (i.e. structured and unstructured data). Businesses can choose to extract data only when they are ready to process it; however, it is best practice to land raw data with a cloud provider first (data warehouse or data lake). This way, business can update historical data if they need to make adjustments to data processing routines. Data Transformation: A series of jobs are executed to process data and transform the data into a format that is required by the destination data repository. Transformation jobs embed automation and governance into the process flow, ensuring that the data is cleaned and transformed accordingly. Data Storage: After data is transformed, the data is then stored within a data repository (commonly, a relational database), where it can be exposed to business stakeholders. Data Pipelines vs ETL Pipelines In many circles, the terms of “data pipeline” and “ETL pipeline” are often interchangeable within a conversation; however, the term “ETL pipeline” should be considered a sub-category of the conversation. Between these two terms of a pipeline, there are distinguished points that need to be understood. ETL Pipelines: follow a specific sequence. As ETL implies, the pipeline extracts data, transform data, and then loads the data into a data repository. Not all data pipelines follow this sequence of events. In fact, changing the order of the processes with an ETL pipeline enables an ELT (Extract, Load, Transform) pipeline. ELT pipelines have be come popular with cloud-native approaches since they do the transformation later in the process. ETL pipelines also tend to imply the use of “batch processing”, but as noted earlier can also be inclusive of stream processing. Data Pipelines: It is unlikely to see a true data pipeline undergo data transformations, like an ETL pipeline. Data pipelines tend to be more focused on feeding data to the end target platform (relational database, data lake, or data warehouse), where additional processes will be used to do the data transformation. Data Pipeline Use Cases With the term “big data” being coined in the 1990’s, the growth of data has continued to grow and projected to reach 180 zettabytes by 2025 (2 years from now). As this growth of data continues, data management and data cleaning becomes an ever-increasing priority and putting more pressure on the use of “data pipelines”. While data pipelines can serve many different functions, the following, broad applications of them within business are mostly seen: Exploratory Data Analysis (EDA): EDA is used by data scientists to analyze and investigate data sets and summarized the sets main characteristics, often employing data visualization methods – making easier for data scientists to discover patterns, spot anomalies, test hypothesis, or check assumptions. Data Visualizations: Representations of data via common graphics (charts, plots, info graphs, etc.). Data visualizations display information and communication of complex data relations and data-driven insights in a way that is easy to understand. Machine Learning (ML/AI): Machine Learning is a sub-branch of Artificial Intelligence (AI) and compute science which focuses on using data and models to imitate the way a human learns, thinks, and gradually improves it accuracy. Through the usage of statistical models, models are trained to make classifications or predictions, uncover key insights within an organization’s data. RheoData Recommendations In the above discussion on Data Pipelines, there is a lot for organizations to think about and how these pipelines may or may not be in place with your organization. Organizations are often looking at the bigger picture or the goal, but not how to transform their existing “pipelines” into more modern approaches of getting data where it is needed. For these reasons, RheoData recommends using the following Oracle products to establish or refresh “data pipelines” and building analytical or machine learning/artificial intelligence (ML/AI) processes today. Oracle GoldenGate / Oracle GoldenGate Service Oracle GoldenGate Steram Processing Oracle Autonomous Data Warehouse / Oracle Autonomous Transaction Processing MySQL Heatwave These products from Oracle can help organizations build robust data pipeline, scalable data lake or data warehouse platforms and ensure timely data processing. Data Pipelines and RheoData RheoData has helped many customers, private and public sectors, gain understanding of their data pipelines and how various Oracle products can be used to enable organizational transformation. Below are a few examples: Shoe Carnival improves data pipeline by upgrading Oracle GoldenGate (here) Altec uses a hyper-volume data pipeline to ingest to Oracle Autonomous Data Warehouse (ADW)(here) American Tire Distributor using Oracle GoldenGate for Big Data to populate Google Cloud Storage (here) Zero-ETL – What is it? (here) Contact Info Give us a call today to schedule a review or build your data pipelines!", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Data Pipelines – What is a data pipeline?", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/datapipelines-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/data-pipelines", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Today, while helping a customer, we had to rebuild an extract. The integrated extract that we rebuilt was stuck in a loop and displaying it was an initial load extract from the HTML5 page (AdminService). The adminclient (cmd line), said it was working fine. After the customer rebooted the their GoldenGate Service (GGS) environment, the integrated extract was still having problems. At this point, we executed an INFO EXTRACT , DETAIL and retrieved the sequence number (EXTSEQ) and the relative byte address (EXTRBA). With this information in hand, we removed the extract and the associated parameter file. After all, we were going to rebuilt the extract. The customer the rebuilt the extract using Microsoft VSCode with the RESTful plug-in (makes it really easy and scriptable). With the integrated extract rebuilt, we attempted to ALTER EXTRACT from the admin service, but there is no options (image 1). Image 1: alter extract no seqno/rba option This lead us to look at altering the extract from AdminClient within GGS. The alter extract command that we use was: adminclient> alter extract , extseq , extrba This command caused a syntax error. For anyone and myself, doing GoldenGate for better part of 15 plus years, this was odd. So, we went and looked up the documentation on ALTER EXTRACT in 19c (here). The command syntax for ALTER EXTRACT for Admin Client is clearly the same as any veteran to Oracle GoldenGate would remember. Admin Client Syntax (19c): ALTER EXTRACT group-name [, BEGIN (NOW | yyyy-mm-dd[ hh:mi:[ss[.cccccc]]]} | EXTSEQNO sequence-number [, EXTRBA archive-offset-number] [, ADD_EXTRACT_attribute] | SCN value] [, DESC [, UPGRADE INTEGRATED TRANLOG] [, DOWNGRADE INTEGRATED TRANLOG [THREADS number]] [, THREAD number] [, ETROLLOVER] [, ENCRYPTIONPROFILE encryption-profile-name ] [CRITICAL [ YES | NO ] [PROFILE profile-name | [AUTOSTART [ YES | NO ] [DELAY delay-number] [AUTORESTART [ YES | NO ]| [RETRIES retries-number ]| [WAITSECONDS wait-number ]| [RESETSECONDS reset-number ]| [DISABLEONFAILURE [ YES | NO ] ] ] ] Then we realized or remembered that we were using GoldenGate Service (GGS) and there might have been a few things different from the 19c release to the 21c release. After all, Oracle GoldenGate Service (GGS) is running on 21c. This prompted me to look at the 21c docs and I was sure it didn’t change; users needed a way to position an extract after rebuilding. The documentation for 21c (here) provide what the syntax is for ALTER EXTRACT in 21c – there are minor differences: Admin Client Syntax (21c): ALTER EXTRACT group-name [, BEGIN {NOW | yyyy-mm-dd[ hh:mi:[ss[.cccccc]]]} | [, EXTRBA archive-offset-number] [, ADD_EXTRACT_attribute] | SCN value] [, DESC [, THREAD number] [, ETROLLOVER] [, ENCRYPTIONPROFILE encryption-profile-name ] [CRITICAL [ YES | NO ] [PROFILE profile-name | [AUTOSTART [ YES | NO ] [DELAY delay-number] [AUTORESTART [ YES | NO ]| [RETRIES retries-number ]| [WAITSECONDS wait-number ]| [RESETSECONDS reset-number ]| [DISABLEONFAILURE [ YES | NO ] ] ] ] [, LOGNUM lognum] [, LOGPOS logpos] What this meant for the customer, is that the extract could be rebuilt; however, to find the correct position to start the extract from we needed to know how to get the correct System Change Number (SCN) or the correct Relative Byte Address (RBA). In discussions with the customer, we decided that it was best to use a known System Change Number (SCN). With the information we had, the customer knew we could go back an hour. From here, we used an old post which I wrote in 2014 on how to convert a timestamp to SCN (here). After the retrieving the SCN, we start the rebuilt extract as follows: adminclient> alter extract , scn The extract started successfully, remained on the correct trail file (we were over 660ish files) and captured data as expected. Lesson learned here was, between versions Oracle likes to change things and we need to keep up. At the same time, we wish subtle differences like this do not get over looked in the release notes.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Interesting change in ALTER EXTRACT command", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/oraclegoldengateserviceALTEREXTRACT-2.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/alter-extract-command", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ```