--- title: RheoData Blog | Oracle Database 26ai description: Oracle Database 26ai | 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 # Oracle Database 26ai ## [Coordinated Replicats: Faster, Lower-Risk GoldenGate Loads](https://rheodata.com/en-us/blog/coordinated-replicats-initial-load) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Jun 26, 2026 11:08:13 AM Every Oracle GoldenGate migration project has a moment where the schedule is won or lost: the... [CONTINUE READING](https://rheodata.com/en-us/blog/coordinated-replicats-initial-load) ## [Why Monolithic Databases Win for AI: GoldenGate & Oracle 26ai](https://rheodata.com/en-us/blog/monolithic-ai-database-goldengate-oracle-26ai) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Dec 16, 2025 8:16:27 PM Let's talk about a challenge I'm seeing across organizations right now: teams are racing to... [CONTINUE READING](https://rheodata.com/en-us/blog/monolithic-ai-database-goldengate-oracle-26ai) ## [Oracle AI World 2025: How RheoData Helps You Accelerate AI with Your Enterprise Data](https://rheodata.com/en-us/blog/oracle-ai-world-2025-accelerate-ai-initiatives-enterprise-data) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:28:58 PM Oracle AI World 2025 delivered exactly what enterprises need: a clear path to making AI work with... [CONTINUE READING](https://rheodata.com/en-us/blog/oracle-ai-world-2025-accelerate-ai-initiatives-enterprise-data) ### 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 ##### 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" : "Oracle Database 26ai | 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/oracle-database-26ai", "@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" : "Every Oracle GoldenGate migration project has a moment where the schedule is won or lost: the initial load. It is the unglamorous part of the plan — move the existing data, then let change data capture keep it current — and it is also where cutover windows quietly blow up. Pick the wrong replicat for a large table and a load you scoped in hours can stretch into the weekend, pushing your go-live and everyone's nerves with it. Here is the straight story: the type of replicat you use for initial load directly affects your project timeline, your cutover risk, and how confidently you can tell the business when you will be live. For loading data, the coordinated replicat is the one that protects the schedule. Let me explain why, and what it means for your migration. TL;DR For Oracle GoldenGate initial loads, the coordinated replicat is the better choice over the parallel replicat — and the difference shows up on your project plan, not just in a config file. Initial load is a timeline risk, not a footnote. The replicat you choose decides whether a large table loads in parallel or becomes your bottleneck. Parallel replicat serializes on a single table, so big single-table loads do not scale — and that is exactly when your cutover window is tightest. Coordinated replicat ships with 25 threads by default and can load even a single table in parallel using THREAD or THREADRANGE(). The change is low-effort, high-leverage. You swap one, maybe two, replicats — the rest of your REST API load process stays the same. RheoData designs and delivers this so your team inherits a repeatable, low-risk load instead of learning it under deadline pressure. Why Initial Load Strategy Belongs on Your Project Plan When leaders ask when can we cut over?, the honest answer depends heavily on how fast the initial load runs. That single number drives the size of your maintenance window, how much downtime the business has to absorb, and how much margin you have if something needs a second pass. Treat initial load as a checkbox and it becomes the line item that slips. Treat it as a design decision and it becomes predictable. The good news is that this is a decision you can get right early, with very little added effort. The rest of this post walks through the mechanics so you understand why the coordinated replicat is the safer bet — and so you can ask the right questions of whoever is delivering your migration. Two Trail File Types: EXTTRAIL vs. EXTFILE The initial load process uses two different kinds of trail files. They look similar, but they do very different jobs, and knowing the difference is the foundation for everything that follows. Trail File What It Holds EXTTRAIL A binary file that houses Change Data Capture (CDC) transactions. EXTFILE A file used for full table dumps of all the data. Your ongoing replication rides on EXTTRAIL. Your initial load rides on EXTFILE. The REST API approach I have written about for years remains the best way to do this, because everything can be scripted — and scripted means repeatable, reviewable, and far less prone to the manual mistakes that cost you a cutover. The SPECIALRUN Change — and Why It Gives You Options When Oracle moved to the RESTful API architecture, it removed the SPECIALRUN parameter from replicats. The practical effect is a win: every replicat can now read both the EXTTRAIL and the EXTFILE formats, which means any replicat can serve as your initial load replicat. You are no longer locked into a special-purpose process just to move the existing data. There is one trade-off to plan for. Without SPECIALRUN, the replicat will not automatically stop once it finishes loading the EXTFILE — so your runbook needs to account for stopping and monitoring it. Oracle calls the unified behavior a feature, and it is; you simply trade the old stop when done convenience for far more flexibility. One detail to keep handy: the last release where SPECIALRUN appears is 19.1. On a current release, it is not coming back. Coordinated vs. Parallel Replicat: The Decision That Moves Your Timeline Across many implementations and tests, I keep landing on the same answer for the initial load of data: the coordinated replicat is the best fit. Both replicat types can do the job, so here is the difference that actually matters to your schedule. Parallel Replicat Parallel replicat lets you set minimum and maximum parallelism, which sounds ideal until you hit the catch: when it is loading a single table, the parallelism serializes and does not scale. Translated to the project plan, your largest table — the one most likely to define your cutover window — loads slower than you planned, exactly when you can least afford it. Coordinated Replicat Coordinated replicat does the same kind of work — it is, in fact, the precursor to parallel replicat — but it carries an advantage that pays off at load time. By default it has 25 threads available, and a single table can be loaded using the THREAD or THREADRANGE() parameter to leverage those pre-allocated threads. The result is a single large table loaded genuinely in parallel — the outcome parallel replicat could not give you, and the one that keeps a big table from becoming your bottleneck. What This Means for Your Cutover Here is the part executives appreciate: adopting this does not mean redesigning your migration. If you already have a REST API initial load process, the only change is switching out one, maybe two, replicats depending on the size of the environment. Same approach, better engine under the hood — and a load you can size with confidence instead of crossing your fingers on cutover night. How RheoData Helps Understanding the difference is step one. Designing, scripting, and delivering an initial load that holds up under a real cutover — with the right replicat architecture, the right thread strategy for your largest tables, and a runbook your team can actually operate — is where most projects want a partner who has done it before. That is what we do at RheoData. We help organizations move and modernize their data on Oracle GoldenGate with migrations and initial loads that are repeatable, observable, and built to protect the schedule. Our work is grounded in deep GoldenGate experience: our founder, Bobby L. Curtis, is an Oracle ACE Director and the author of Pro Oracle GoldenGate 23ai for the DBA. When we hand a project back to your team, they inherit something they can run, not a black box. Whether you are planning your first GoldenGate migration or tightening a cutover window that has burned you before, we would welcome the conversation. FAQ Why does initial load strategy affect my project timeline? The speed of the initial load determines how large your cutover and maintenance window must be. A load that does not scale on your biggest table directly extends downtime and pushes your go-live, which is why the replicat choice is a planning decision, not just a technical one. Why is the coordinated replicat better than the parallel replicat for initial load? The coordinated replicat ships with 25 threads by default and can load a single table in parallel using THREAD or THREADRANGE(). The parallel replicat serializes parallelism on a single table, so large single-table loads do not scale and take longer. What is the difference between EXTTRAIL and EXTFILE in Oracle GoldenGate? EXTTRAIL is a binary file that houses Change Data Capture (CDC) transactions. EXTFILE is a file used for full table dumps of all the data. Initial loads rely on EXTFILE, while ongoing replication relies on EXTTRAIL. Do I have to rebuild my migration to use a coordinated replicat? No. The overall REST API initial load process stays the same. You are only swapping out one, possibly two, replicats depending on the size of the environment being loaded. Can RheoData help with our GoldenGate migration? Yes. RheoData designs and delivers Oracle GoldenGate migrations and initial loads, including the replicat architecture and scripting that keep cutovers low-risk and repeatable. Reach out and we will scope it with you. Let's Talk If you are sizing a GoldenGate migration or want a second set of eyes on an initial load before it lands on a cutover plan, let's connect. Visit rheodata.com or email bobby.curtis@rheodata.com. Clear objectives, team success — that is how we run every engagement.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "26/06/2026", "datePublished" : "26/06/2026", "headline" : "Coordinated Replicats: Faster, Lower-Risk GoldenGate Loads", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Gemini_Generated_Image_509fjc509fjc509f.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/coordinated-replicats-initial-load", "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" : "Let's talk about a challenge I'm seeing across organizations right now: teams are racing to implement AI solutions, but their data pipelines can't keep pace with what AI models actually need. At RheoData, we've watched companies invest millions in cutting-edge AI capabilities only to have their initiatives stall because their data infrastructure wasn't built for the real-time, high-quality data flows that AI demands. Here's the story—AI is only as good as the data feeding it. Your models need fresh, accurate, consistent data flowing continuously. Miss any of these elements, and you're building on a shaky foundation. This is exactly why we've focused our practice on building AI-ready data frameworks that address these fundamental challenges. The Real Problem with Traditional AI Data Pipelines In our work helping enterprises transform their data infrastructure, we keep seeing the same pain points. Traditional batch processing creates data lag that renders AI insights stale before they're actionable. Data quality issues multiply across systems, creating inconsistencies that AI models struggle to handle. And when you're moving data between on-premises systems and cloud platforms, the complexity compounds quickly. What does this look like in practice? Your fraud detection model is working with yesterday's transaction data. Your customer recommendation engine is making suggestions based on outdated inventory. Your predictive maintenance AI is analyzing equipment data that's hours old when seconds matter. These aren't just technical problems—they're business problems that impact your competitive position. At RheoData, we've built our expertise around solving exactly these challenges, helping organizations create data pipelines that actually deliver on AI's promise. How Oracle GoldenGate Changes the Game Oracle GoldenGate has been a cornerstone of data replication for years, but its value for AI pipelines is often underestimated. Through our implementation work across multiple industries, we've identified what makes it particularly powerful for AI workloads. Real-Time Data Movement GoldenGate captures and replicates data changes as they happen—we're talking milliseconds, not hours. For AI applications, this means your models are working with current data. We've implemented GoldenGate architectures where fraud detection models now analyze transactions in near real-time instead of hours later. Recommendation engines reflect inventory changes immediately. Predictive models are actually predictive instead of reactive. Bidirectional Replication for Hybrid Environments Most organizations aren't living in a single cloud or purely on-premises anymore. At RheoData, we specialize in complex hybrid architectures—we handle bidirectional replication seamlessly, whether you're moving data between on-premises Oracle databases and OCI, integrating with Google Cloud Platform, or maintaining data consistency across multiple clouds. Your AI pipeline doesn't need to care where the data lives—we architect GoldenGate topologies that ensure data flows where it needs to go. Data Transformation in Transit Here's where our expertise becomes particularly valuable for AI workloads. GoldenGate doesn't just move data—we configure it to transform data during replication. Filter out irrelevant records. Mask sensitive information to maintain compliance. Aggregate data for specific AI model requirements. You're not just replicating data; we're preparing it for AI consumption on the fly. Minimal Impact on Source Systems We've seen too many data integration projects bog down production systems. GoldenGate uses a log-based approach that reads transaction logs rather than querying tables directly. In our implementations, operational systems keep running at full speed while AI pipelines get the data they need—a critical balance we maintain in every architecture we design. Oracle Database 26ai: Purpose-Built for AI Workloads Now let's talk about Oracle Database 26ai, which Oracle is positioning specifically for AI and machine learning workloads. At RheoData, we've been working with Oracle's AI-enhanced database capabilities since their early releases, and we're seeing meaningful enhancements that address AI-specific challenges. Vector Search Capabilities Database 26ai includes native vector search functionality. If you're working with large language models, embeddings, or similarity searches—common requirements for modern AI applications—you can now store and query vector data directly in the database. We've architected solutions that eliminate separate vector databases, reducing integration complexity and improving performance. In-Database Machine Learning Oracle Machine Learning is deeply integrated, allowing you to build, train, and deploy models directly where your data lives. We help data science teams work directly with production data (appropriately secured, of course) without complex extract-transform-load processes. The result? Faster model training and simplified architecture. AI-Optimized Performance Database 26ai includes optimizations for AI query patterns. When you're running complex analytical queries to train models or serving predictions at scale, these optimizations translate to faster model training and lower-latency predictions. Our team tunes these configurations to match your specific AI workload patterns. Automated Data Management AI workloads are data-intensive. Database 26ai includes enhanced autonomous capabilities that automatically tune performance, manage storage, and optimize query execution based on AI workload patterns. We layer our governance and monitoring frameworks on top of these capabilities to ensure your database administration teams focus on strategy rather than constant tuning. Bringing It Together: The RheoData AI Framework Approach Here's where GoldenGate and Database 26ai become particularly powerful together, and where RheoData's expertise delivers real value. Let me walk through the framework architecture we've refined across multiple client implementations. Real-Time Data Ingestion We configure GoldenGate to continuously capture changes from your operational databases—Oracle, SQL Server, MySQL, whatever you're running. These changes flow in real-time to Database 26ai, where they're immediately available for AI model consumption. In our implementations, data freshness goes from hours or days to seconds. Hybrid Cloud Flexibility Your operational systems might be on-premises, your data lake in Google Cloud Platform, and your AI training environment in OCI. At RheoData, we're experts in both Oracle and Google Cloud ecosystems—we architect the connectivity and data flow across all of these environments. Database 26ai can sit at any point in this architecture, serving as your AI-optimized data platform wherever it makes sense for your workload. Data Quality and Preparation As we configure GoldenGate to move your data, we implement transformations and quality checks based on your AI model requirements. By the time data reaches Database 26ai, it's clean, properly formatted, and ready for AI consumption. Your data scientists spend time building models instead of cleaning data—exactly what we aim for in every engagement. Unified Data Access We design Database 26ai as a single point of access for your AI applications. Whether you're training models, serving real-time predictions, or running analytical queries, you're working with consistent, current data. No more data silos creating conflicting results. Implementation Considerations: The RheoData Methodology Let's talk about what it takes to make this work in your environment. At RheoData, we've developed a proven methodology for implementing AI-ready data frameworks. Start with Your AI Use Cases We don't build infrastructure in search of a problem. Our engagements start by identifying your AI initiatives that are being constrained by data pipeline limitations. Where would real-time data make a meaningful business difference? Which AI workloads are struggling with data quality or freshness? We help you focus effort where it delivers the most value. Design for Data Governance Real-time data flows are powerful, but they need proper governance. We build in data quality checks, establish clear ownership, and ensure compliance requirements are met as data moves through your pipelines. Our team leverages GoldenGate's transformation capabilities to embed governance into the data flow itself. Architect Your Hybrid Environment We're realistic about where your data lives now and where it needs to be. Most organizations are operating in hybrid environments, and RheoData specializes in these complex architectures. We design GoldenGate topologies that handle your current reality while being flexible enough to adapt as your environment evolves. Implement Comprehensive Monitoring Real-time pipelines need real-time monitoring. We implement comprehensive monitoring for GoldenGate replication lag, Database 26ai performance metrics, and data quality indicators. You can't manage what you can't measure—we ensure you have visibility into every aspect of your AI data pipeline. Build Team Capabilities Your team needs to understand both GoldenGate administration and AI workload optimization in Database 26ai. RheoData provides training and knowledge transfer as part of every implementation. The best architecture fails without teams capable of operating it effectively, and we ensure your teams are equipped for long-term success. The RheoData Advantage What makes RheoData different in this space? We bring deep expertise across the entire Oracle and Google Cloud ecosystems. Our team has implemented complex data replication architectures for decades, and we've evolved that expertise specifically for AI workloads. We understand both the strategic business requirements and the tactical implementation details that make the difference between a proof of concept and a production system that delivers business value. We don't just implement technology—we build frameworks that your teams can operate, maintain, and evolve. Our goal is your team's success, and we measure our success by the AI capabilities you're able to deploy after we've worked together. Moving Forward: Let's Execute on This AI is transforming how organizations operate, but success requires infrastructure that can keep pace with AI demands. Oracle GoldenGate and Database 26ai provide a powerful foundation for building resilient, real-time AI data pipelines that can scale with your ambitions. The question isn't whether you need better data infrastructure for AI—you do. The question is whether you're ready to address it strategically before data pipeline limitations constrain your AI initiatives. At RheoData, we've built our practice around helping organizations like yours implement AI-ready data frameworks that deliver results. What does success look like here? AI models that work with current data. Faster time-to-insight. Simplified architecture that your teams can operate. And the flexibility to adapt as your AI strategy evolves. I'd value your perspective on this. What data pipeline challenges are you seeing with your AI initiatives? Where are traditional approaches falling short? Let's continue this conversation—reach out to our team at RheoData - cloud@rheodata.com - and we'll explore how we can help you build the data infrastructure your AI strategy deserves.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "16/12/2025", "datePublished" : "16/12/2025", "headline" : "Why Monolithic Databases Win for AI: GoldenGate & Oracle 26ai", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Gemini_Generated_Image_zfy4knzfy4knzfy4.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/monolithic-ai-database-goldengate-oracle-26ai", "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" : "Oracle AI World 2025 delivered exactly what enterprises need: a clear path to making AI work with their existing data infrastructure. The announcements coming out of Las Vegas this year aren’t just impressive from a technical standpoint—they’re strategically significant for any organization that’s been asking the question: “How do we actually implement AI with our enterprise data?” Oracle’s answer is now crystal clear, and at RheoData, we’re ready to help you execute on that vision. Let me share what Oracle announced and, more importantly, how RheoData can help your organization leverage these innovations to accelerate your AI initiatives. The Oracle ACE Community: Where Expertise Meets Innovation One of the highlights of Oracle AI World was reconnecting with the Oracle ACE community—a network of technical experts who share knowledge and drive innovation across the Oracle ecosystem. At RheoData, we’re proud to be part of this community and bring that same collaborative spirit to every client engagement. The Oracle ACE Apprentice program continues to grow, offering professionals at all levels the opportunity to expand their skills and build their networks. This commitment to knowledge sharing is exactly what makes Oracle technologies so powerful—there’s an entire community dedicated to helping organizations succeed. When you work with RheoData, you’re not just getting a vendor. You’re getting partners who are deeply embedded in the Oracle community, who understand the latest innovations, and who have direct connections to the experts driving these technologies forward. Oracle Database 26ai: AI Architected Into Your Data Here’s the game-changer: Oracle Database 23ai has become Oracle Database 26ai, and this transformation represents Oracle’s bold vision of architecting AI directly into the core of data management. What Oracle announced: Oracle AI Database 26ai replaces Oracle Database 23ai with a massive expansion of AI capabilities across AI Vector Search, Agentic AI, AI management, AI Data Development, AI Analytics, and AI App Development. This is Oracle’s “AI for Data” strategy in action—making AI simple to learn, simple to use, and integrated throughout your entire data stack. The transition is remarkably straightforward. If you’re running 23ai, you apply the October 2025 quarterly Release Update. No complex upgrade. No application recertification. If you’re on 19c or 21c, you can upgrade directly to 26ai. For Autonomous Database customers, the upgrade happens automatically. Why this matters for your business: Your enterprise data is your most valuable asset, and now Oracle has made it AI-ready without requiring you to move data, rebuild applications, or sacrifice the reliability your business depends on. Oracle AI Database 26ai enables you to run dynamic agentic AI workflows that combine your private database data with public information to deliver sophisticated insights and actions. Advanced AI features like AI Vector Search are included at no additional charge. The platform supports the tools and frameworks your team wants to use—Apache Iceberg, Model Context Protocol, industry-leading LLMs, popular agentic AI frameworks, and ONNX embedding models. How RheoData accelerates your Database 26ai journey: At RheoData, we specialize in Oracle Database transformations and AI strategy. Here’s what we bring to your Database 26ai initiative: Strategic Assessment: We evaluate your current database environment and create a clear roadmap for leveraging Database 26ai’s AI capabilities Seamless Migration: Whether you’re upgrading from 19c, 21c, or 23ai, we ensure a smooth transition with zero downtime strategies AI Use Case Development: We help you identify and implement high-value AI use cases that leverage your existing enterprise data Performance Optimization: Our team ensures your Database 26ai deployment is architected for maximum performance and scalability Ongoing Support: We provide the expertise you need to continuously evolve your AI capabilities as Oracle releases new features We’ve guided numerous organizations through complex Oracle Database transformations, and we understand how to make these initiatives successful while minimizing disruption to your operations. Oracle GoldenGate: The Real-Time Data Foundation for AI Oracle GoldenGate has always been the gold standard for real-time data replication and integration, and the announcements at AI World 2025 reinforce why it’s essential for organizations building AI-ready data platforms. Key GoldenGate capabilities announced: Certifications for Oracle AI Data Platform and Autonomous AI Lakehouse — GoldenGate now integrates seamlessly with Oracle’s AI-optimized environments, eliminating ETL complexity and accelerating time to insights. GoldenGate for MongoDB Migrations 26ai — Expanding GoldenGate’s any-to-any integration capabilities for heterogeneous data environments. Enhanced Multicloud Architecture — Deploy GoldenGate across OCI, AWS, Azure, and Google Cloud with consistent performance and reliability. Tighter Integration with Database 26ai — Support for vector data types, JSON Relational Duality Views, and GoldenGate Data Streams enables real-time, event-driven AI architectures. Air-Gapped Replication — Deploy in Oracle Network Security Group environments for organizations with the strictest security requirements. GoldenGate Free — Enterprise-grade replication technology available for development, testing, and proof-of-concept projects. Why GoldenGate is critical for your AI strategy: AI requires fresh, accurate data. GoldenGate provides real-time change data capture and replication that ensures your AI models and analytics always work with current information. Whether you’re building machine learning pipelines, real-time analytics dashboards, or agentic AI applications, GoldenGate creates the data foundation that makes these initiatives successful. How RheoData implements GoldenGate for AI success: RheoData has deep expertise in Oracle GoldenGate across all deployment scenarios—on-premises, cloud, and hybrid. Here’s how we help organizations leverage GoldenGate for their AI initiatives: Real-Time Data Architecture: We design and implement GoldenGate solutions that feed your AI platforms with continuously updated data Multicloud Integration: We connect your Oracle databases with Azure, AWS, and Google Cloud analytics and AI services using GoldenGate High Availability: We architect GoldenGate deployments that ensure your data replication never becomes a single point of failure Performance Tuning: We optimize GoldenGate for maximum throughput and minimal latency in high-volume environments Migration Expertise: We use GoldenGate to enable zero-downtime migrations to cloud platforms while maintaining business continuity Our team has successfully implemented GoldenGate for organizations processing millions of transactions daily, and we understand the nuances of making real-time replication work at enterprise scale. OCI GoldenGate on Azure: Breaking Down Cloud Barriers The general availability of OCI GoldenGate integration with Oracle Database@Azure is transformational for organizations committed to Azure as their cloud platform. What this integration enables: Organizations can now run OCI GoldenGate natively in Azure data centers and manage it through the Azure console, providing seamless real-time data synchronization between Oracle databases and Azure services like Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage, Azure Event Hubs, and Microsoft Fabric. The integration delivers minimal latency, unified management through Microsoft Entra ID, and creates true real-time AI pipelines by combining GoldenGate’s change data capture with Azure AI services. Oracle Database Mirroring in OneLake (now in public preview) provides low-cost, low-latency mirroring of Oracle databases directly into Microsoft Fabric’s OneLake in Delta Lake–optimized format, eliminating complex ETL pipelines. How RheoData maximizes your Azure + Oracle investment: At RheoData, we specialize in multicloud architectures that leverage the best of both Oracle and Microsoft technologies. Here’s how we help: Azure Integration Strategy: We design solutions that seamlessly integrate Oracle Database@Azure with your existing Azure ecosystem GoldenGate on Azure Implementation: We deploy and configure OCI GoldenGate in Azure for optimal performance and reliability Microsoft Fabric Integration: We connect your Oracle data to Microsoft Fabric, Power BI, and Copilot Studio for comprehensive analytics and AI Cost Optimization: We architect solutions that maximize value while minimizing data movement costs across cloud platforms Security and Compliance: We ensure your multicloud data flows meet your organization’s security and regulatory requirements We understand both the Oracle and Azure ecosystems deeply, and we know how to make them work together to deliver measurable business value. Your Data. Your AI. Our Expertise. Oracle AI World 2025 made one thing abundantly clear: the AI revolution isn’t about replacing your existing data infrastructure—it’s about making that infrastructure AI-ready. Oracle Database 26ai and the enhanced GoldenGate platform provide the technical foundation. What you need now is a partner who can help you execute on that vision with your specific data, your unique business requirements, and your strategic objectives. That’s where RheoData comes in. We bring decades of combined experience in Oracle Database, Oracle GoldenGate, cloud architecture, and AI strategy. We’ve helped organizations across industries transform their data platforms to support real-time analytics, machine learning, and AI-driven decision making. We understand the technical complexities, the organizational challenges, and the business imperatives that drive these initiatives. What makes RheoData different: Deep Oracle Expertise: We’re Oracle technology specialists with extensive experience in Database, GoldenGate, and OCI AI Strategy Focus: We don’t just implement technology—we help you identify and execute on high-value AI use cases Multicloud Proficiency: We architect solutions across Oracle Cloud, Azure, AWS, and Google Cloud based on your needs Results-Driven Approach: We focus on delivering measurable business outcomes, not just technical implementations Partnership Mindset: We work alongside your team, transferring knowledge and building capabilities for long-term success Ready to Accelerate Your AI Initiatives? The technologies announced at Oracle AI World 2025 create unprecedented opportunities for organizations to leverage AI with their enterprise data. The question isn’t whether to pursue these opportunities—it’s how to execute effectively. RheoData has the expertise, experience, and strategic approach to help your organization: ✓ Upgrade to Oracle Database 26ai and unlock AI capabilities with your existing data ✓ Implement Oracle GoldenGate for real-time data integration across your enterprise ✓ Integrate Oracle technologies with Azure, AWS, or Google Cloud for multicloud AI platforms ✓ Design and deploy AI-ready data architectures that scale with your business ✓ Build high-value AI use cases that deliver competitive advantages Let’s start the conversation. If you’re ready to transform your enterprise data into an AI-ready strategic advantage, we’re ready to help you execute on that vision. Contact RheoData today: 📧 cloud@rheodata.com Our team will work with you to understand your objectives, assess your current environment, and create a clear roadmap for leveraging Oracle Database 26ai, GoldenGate, and AI technologies to achieve your business goals. The AI revolution is here. Your data is ready. Let’s execute together.", "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" : "Oracle AI World 2025: How RheoData Helps You Accelerate AI with Your Enterprise Data", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/Gemini_Generated_Image_pf53s7pf53s7pf53-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/oracle-ai-world-2025-accelerate-ai-initiatives-enterprise-data", "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" } } ```