--- title: RheoData Blog | Cloud (2) description: Cloud | RheoData Blog Posts (2) --- [![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 # Cloud (2) ## [Capturing Stats by time](https://rheodata.com/en-us/blog/capturing-stats-by-time) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:49 PM With Oracle GoldenGate there are times when you want to know the number of DML that is being pushed... [CONTINUE READING](https://rheodata.com/en-us/blog/capturing-stats-by-time) ## [Oracle to GCP Migration: Oracle@GCP vs. Cloud SQL – The Strategic Choice That Drives Results](https://rheodata.com/en-us/blog/oracle-gcp-vs-cloud-sql-migration) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:47 PM The partnership between Oracle and Google Cloud represents one of the most significant... [CONTINUE READING](https://rheodata.com/en-us/blog/oracle-gcp-vs-cloud-sql-migration) ## [Access Oracle DBCS Pluggable Database via Bastion Connection](https://rheodata.com/en-us/blog/access-oracle-dbcs-pluggable-database-via-bastion-connection) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:47 PM What is a Bastion? [CONTINUE READING](https://rheodata.com/en-us/blog/access-oracle-dbcs-pluggable-database-via-bastion-connection) ## [Replicating PostgreSQL data using Oracle GoldenGate](https://rheodata.com/en-us/blog/replicating-postgresql-data-using-oracle-goldengate) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:46 PM Something that has been brewing for years – since late 2017 – is the constant request from Oracle... [CONTINUE READING](https://rheodata.com/en-us/blog/replicating-postgresql-data-using-oracle-goldengate) ## [Hyper Data Ingestion with Oracle GoldenGate Service (GGS)](https://rheodata.com/en-us/blog/hyper-data-ingestion-with-oracle-goldengate-service-ggs) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:45 PM Data ingestion is always the beginning stages of getting data into a data warehouse and/or cloud.... [CONTINUE READING](https://rheodata.com/en-us/blog/hyper-data-ingestion-with-oracle-goldengate-service-ggs) ## [Performance with Oracle GoldenGate](https://rheodata.com/en-us/blog/performance-with-oracle-goldengate) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:45 PM [CONTINUE READING](https://rheodata.com/en-us/blog/performance-with-oracle-goldengate) ## [Zero-ETL: What is it and what Oracle products support it](https://rheodata.com/en-us/blog/zero-etl) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:41 PM Businesses are constantly finding themselves increasingly reliant on data ingestion, big data,... [CONTINUE READING](https://rheodata.com/en-us/blog/zero-etl) ## [Removing a MySQL Heatwave Cluster](https://rheodata.com/en-us/blog/removing-a-mysql-heatwave-cluster) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:41 PM Recently I’ve been playing with Oracle’s MySQL Database Service (MDS) and testing out the Heatwave... [CONTINUE READING](https://rheodata.com/en-us/blog/removing-a-mysql-heatwave-cluster) ## [A simple way to stop all Docker containers](https://rheodata.com/en-us/blog/a-simple-way-to-stop-all-docker-containers) Posted by [rheostage5132](https://rheodata.com/en-us/blog/author/rheostage5132) | Nov 10, 2025 9:30:10 PM This is just a quick reminder post to illustrate how to stop all docker containers that are running... [CONTINUE READING](https://rheodata.com/en-us/blog/a-simple-way-to-stop-all-docker-containers) ## [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... 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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" : "Cloud | RheoData Blog Posts (2)", "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/cloud/page/2", "@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 Oracle GoldenGate there are times when you want to know the number of DML that is being pushed through the system. Oracle provides this through the STATS command from within AdminClient (new GGSCI); but what if you want to capture this information on the fly while processing is happening. How would you accomplish this? In this post, I’ll outline what I did for a customer to help them achieve this use-case and provide some feedback. The items used are completely customizable and can be used for any environment. As I started to break down this use-case, I wanted to do something that wasn’t tied directly to the replicat process, but would get the information as it was flowing in and then place it into a table called HIST_STATS. The goal was to capture the amount of DML coming in on a timed basis. The table HIST_STATS is setup as follows: create table tpc1.hist_stats ( table_name varchar2(30), op_date timestamp, inserts number, updates number, deletes number, truncates number, primary key (table_name, op_date) ); Notice that the table is in the TPC1 schema, but in reality it can be in any schema that Oracle GoldenGate has access to. I just choose to put it the same schema as the target tables. At the same time, the PK is set to be table_name and operations date (op_date). This is to ensure that I get all the tables at least once and order the stats by date when they come in. Outside of the PK, I’m just capturing the standard DML (inserts, updates, deletes, and truncates). Keep in mind that truncates really are DDL within Oracle GoldenGate; expectation is that this column should always be zero (0) unless DDL is enabled. With the table set, now I need to configure Oracle GoldenGate to apply this information from the trail file that the replicat reads. The easiest way of doing this is to use the header information in the trail file. I have written a previous blog post on this over on dbasolved.com, check it out. In order to read this information and place it into the HIST_STATS table, the approach I took was to use a macro. The macro that I defined was the following: MACRO #stats_handler PARAMS(#user) BEGIN , TARGET #user.hist_stats , COLMAP ( table_name = @GETENV ('GGHEADER', 'TABLENAME') , op_date = @DATE ('YYYYMMDD HH:MI:SS', 'JTS', @GETENV('JULIANTIMESTAMP')) , inserts = @GETENV ('STATS', 'TABLE', '#user.*','INSERT') , updates = @GETENV ('STATS', 'TABLE', '#user.*','UPDATE') , deletes = @GETENV ('STATS', 'TABLE', '#user.*','DELETE') , truncates = @GETENV ('STATS', 'TABLE', '#user.*','TRUNCATE') ) END; Macros are great for compartmentalizing logic needed to do things within Oracle GoldenGate. They allow GoldenGate Administrators to simplify and automate work within the replication stream (more information here). I’m not going to spend a lot of time explain this macro, but the general definition of it is that I’m capturing the information I’m looking for out of the trail file header using the @GETENV command and mapping it to the target table of HIST_STATS. One thing to note is that the #user is a variable that is being passed to the macro. This allows for the macro to be used anywhere with any schema (doesn’t hard code the user information). At the same time, getting the date down to the second to make sure data is unique for the stats captured. With the macro created, it now needs to be mapped directly into the replicat. This is done by using the INCLUDE option, then adding a MAP statement that calls the macro. replicat REP useridalias PDBGGATE domain OracleGoldenGate REPERROR(1403, discard) REPERROR(1, discard) INCLUDE ./dirmac/stats.mac MAP devdb1.tpc.*, #stats_handler(tpc1); MAP devdb1.tpc.*, TARGET tpc1.*; When you looking at the parameter file for the replicat, you see that there is a directory called dirmac. This is a customer directory that I use to store the macros. Within Oracle GoldenGate Microservices, which I was using, this directory needs to be created under $DEPLOYMENT_HOME/etc/conf/ogg. This is the default location for parameter files within the Microservices architecture. Once this is created and the macro located there, then the next line is a MAP statement that tells GoldenGate that for every table coming in insert the DML stats by calling the macro. This happens before data is actually applied to the tables in the second MAP statement. As data is flowing, you will be able to query the HIST_STATS table and validate that data and DML stats are coming in. In the example below, I’m querying the HIST_STATS table to show only a single table: select * from tpc1.hist_stats where table_name like ‘%ORDERS’ order by op_date asc; The results returned are similar to the image: As you can tell, I can quickly tell the number of cumulative inserts and updates that are happening on the Orders table every second. There is more that can be done with this to find out the insert/update differences per second, but for the general use-case purposes this shows how it can be done. Enjoy!!!", "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" : "Capturing Stats by time", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/macro_stats_hist-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/capturing-stats-by-time", "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" : "The partnership between Oracle and Google Cloud represents one of the most significant collaborative achievements in enterprise technology. Oracle Database@Google Cloud Platform brings together Oracle’s proven database excellence with Google Cloud’s industry-leading infrastructure and AI capabilities, creating unprecedented opportunities for enterprise digital transformation. This strategic alliance enables organizations to leverage Oracle’s advanced database technologies – including Oracle Database 23ai with its revolutionary AI features – while gaining full access to Google Cloud’s comprehensive service portfolio including BigQuery, Vertex AI, and Kubernetes Engine. The result is a unified platform that eliminates the traditional trade-offs between database capability and cloud innovation. As a someone who has led multiple enterprise Oracle migrations and working closely with Google Cloud’s enterprise sales team, we’ve witnessed this partnership deliver exceptional results for organizations seeking to modernize their data infrastructure. While Google Cloud SQL platforms offer solid managed database services for many use cases, Oracle@GCP provides enterprise-grade capabilities that drive competitive advantage and long-term strategic value. Two Paths, One Clear Winner We recently collaborated on evaluating two distinct migration architectures for a client modernizing their Oracle infrastructure on Google Cloud Platform. The contrast illuminated fundamental differences that every IT leader should understand. Path 1: Migration to Google Cloud SQL – A Viable Alternative Google Cloud SQL provides excellent managed database services with PostgreSQL, MySQL, and SQL Server options. These platforms offer strong operational benefits including automated backups, security patching, and high availability configurations. For organizations with simpler database requirements or those looking to standardize on open-source technologies, Cloud SQL represents a solid foundation for cloud operations. However, organizations with complex Oracle workloads may find that Cloud SQL requires additional planning for feature compatibility, performance optimization, and application integration considerations. Path 2: Oracle@GCP with Oracle Database 23ai – The Enterprise Excellence Platform Oracle@GCP deploys Oracle Database through Oracle’s cloud infrastructure services directly within Google Cloud Platform. This architecture provides seamless integration with Google Cloud services while maintaining Oracle’s advanced database capabilities, delivering transformation rather than mere platform conversion. The business case extends beyond technical considerations – it’s about maintaining competitive advantage while achieving cloud benefits. The Oracle 19c Support Reality: A Ticking Clock Based on Oracle’s official Lifetime Support Policy (effective June 10, 2025), Oracle 19c presents significant timeline constraints that both technical and sales perspectives must address: Premier Support ends December 2029 – Only four years of full support remaining from today Extended Support ends December 2032 – Seven-year limited runway with restrictions Java 8 support exclusion after December 2030 – Critical limitation for enterprise environments running integrated Java components Compare this to Oracle 21c (Innovation Release), which offers Premier Support only until July 2027 with no Extended Support available. The pattern is clear: investing in any Oracle release except 23ai means planning replacement before achieving full ROI.Our joint analysis shows that organizations choosing Oracle 19c today will face another migration decision within 3-4 years – creating compounded migration costs and technical debt accumulation. Oracle Database 23ai: Purpose-Built for AI-Powered Enterprise Success Oracle Database 23ai delivers over 300 enterprise-grade features designed for competitive differentiation. From our combined technical and sales perspective, these transformational capabilities drive measurable business outcomes: AI Vector Search integrates semantic search across documents, images, and unstructured data with your private business information – no data movement required, maintaining security while unlocking insights that Google Cloud SQL platforms cannot match. JSON Relational Duality eliminates the traditional document versus relational trade-off by providing unified access through both SQL and JSON APIs, surpassing the capabilities of standard PostgreSQL or MySQL JSON handling. Model Context Protocol (MCP) Integration enables direct AI assistant integration with built-in security, allowing agents to generate and execute SQL queries while maintaining enterprise governance – functionality unavailable in Google Cloud SQL managed services. Oracle True Cache delivers automatically managed, in-memory SQL and key-value caching that accelerates application performance beyond what Cloud SQL memory configurations can achieve. These aren’t incremental improvements – they’re foundational capabilities that position organizations for the next decade of data-driven competition within Google Cloud’s ecosystem. Why Oracle@GCP Wins the Total Cost Analysis Our comprehensive migration assessment reveals the hidden costs of Oracle-to-Cloud SQL conversion that impact bottom-line results: The 80/20 Reality of Database Migration While basic table structures may convert between platforms, they represent only 15-20% of total migration effort. The remaining 80% includes: PL/SQL to stored procedure conversion (60% of effort) – Complete rewriting for PostgreSQL functions or MySQL procedures Application integration changes (20% of effort) – ORM modifications, connection handling, query syntax adjustments Advanced feature reimplementation (10% of effort) – Partitioning, triggers, and constraints require platform-specific approaches Performance optimization (10% of effort) – Completely different tuning methodologies and capabilities Hidden Considerations for Cloud SQL Migration While Google Cloud SQL migration is certainly achievable, organizations should plan for several implementation aspects: Feature adaptation: Some Oracle-specific functionality may require alternative approaches in PostgreSQL, MySQL, or SQL Server environments Application integration updates: Connection handling, query optimization, and ORM configurations may need adjustment for different database engines Performance tuning methodology: Each Cloud SQL platform has unique optimization approaches that teams will need to master Operational procedures: Database administration practices will require updates for the new platform environments Oracle@GCP Advantage Through Partnership Our clients achieve immediate ROI through preserved investments: Zero application rewrite – Existing PL/SQL code base remains fully functional Retained expertise – Current Oracle DBA skills continue delivering value Maintained performance characteristics – No unknown optimization requirements across multiple platforms Preserved advanced features – Partitioning, advanced analytics, and enterprise security remain intact Strategic Positioning for Long-Term Success Oracle@GCP provides the enterprise foundation your organization needs for sustained competitive advantage within Google Cloud’s ecosystem: Google Cloud Integration Excellence – Oracle’s infrastructure services enable seamless connectivity to BigQuery for analytics, AI Platform for machine learning, Kubernetes Engine for containerization, and Vertex AI for advanced AI/ML workloads while maintaining Oracle’s database excellence. AI-Driven Competitive Advantage – Oracle’s built-in AI capabilities complement Google Cloud’s machine learning and analytics services, positioning organizations at the forefront of data-driven decision making. Performance Scalability – Enterprise-grade database performance that surpasses Cloud SQL limitations, particularly for complex analytical workloads and high-concurrency applications that leverage Google Cloud’s compute infrastructure. Operational Excellence – Unified database management with transparent pricing eliminates the complexity of managing multiple Cloud SQL instances for different workload types. The Partnership Perspective: Technical Leadership Meets Sales Excellence From the RheoData View: Oracle@GCP eliminates the technical risks associated with platform conversion while providing immediate access to Google Cloud’s innovation ecosystem. Your team maintains their Oracle expertise while gaining access to best-in-class cloud services. From the Google Cloud Sales Perspective: Oracle@GCP accelerates customer success on Google Cloud Platform by eliminating migration blockers and reducing project risk. Customers achieve faster time-to-value and higher platform adoption rates when database complexity is removed from the equation. Combined Value: This partnership approach ensures both technical success and business objectives align, creating sustainable competitive advantage through proven technology integration. Our Joint Recommendation The data tells a compelling story: Oracle 19c represents a short-term fix when your organization requires long-term strategic advantage. With only four years of Premier Support remaining and Java 8 limitations creating operational constraints, this path misaligns with sustainable operational excellence. Oracle Database 23ai via Oracle@GCP delivers the platform foundation necessary for competitive differentiation over the next 5-10 years. This approach provides true digital transformation – not just database conversion – positioning your organization for sustained success in an AI-powered marketplace while maximizing Google Cloud Platform investments. The Bottom Line for Executive Decision-Making When evaluating Oracle migration options within Google Cloud Platform, consider this strategic question: Does your organization want to invest in a complex multi-platform conversion requiring extensive reengineering, or maintain proven database excellence while gaining cloud benefits? Google Cloud SQL platforms serve specific use cases well, but they cannot match Oracle Database’s enterprise capabilities, advanced analytics features, or AI integration potential. Organizations with significant Oracle investments achieve better ROI by leveraging Oracle@GCP rather than pursuing costly platform conversions. We recommend proceeding with an Oracle@GCP proof of concept to validate performance characteristics and integration capabilities with your specific Google Cloud services. This strategic approach balances innovation with risk management while maintaining business continuity and maximizing both Oracle and GCP investment returns. Contact RheoData at cloud@rheodata.com to discuss how Oracle@GCP can accelerate your organization’s Google Cloud adoption while eliminating the risks and costs associated with heterogeneous database conversion.", "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 to GCP Migration: Oracle@GCP vs. Cloud SQL – The Strategic Choice That Drives Results", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/Gemini_Generated_Image_3gph3a3gph3a3gph-1.jpg", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/oracle-gcp-vs-cloud-sql-migration", "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" : "What is a Bastion? There a three primary definition for the word Bastion. They are: A projecting part of a fortification A fortified area or position A place of security or survival In all three of these definitions, a bastion is a secure place. Within cloud environments security is one of the biggest things to worry about, after all you don’t want to have your databases broadcasting on a public ip address. What is the answer then; well the answer is to keep all items on a private subnet/network and access these resources through a “bastion” host. Below is a simple network architecture that illistrates how to access our testing PDB via a bastion connection. This is a secure way for accessing our database when needed while not broadcasting it publicly. From the network architecture above, it looks pretty straight forward on how to connect to the PDB which is in the Fault Domain 2. In really, to make this connection, we need to create the Bastion host then enable the bastion to connect via ip address to the database. Find the Database Host IP and other information The first thing we need to do is find the database host ip address. This address will be a private IP address of where the database is running. This can easily be found by going to: Overview -> Oracle Base Database -> DB Systems Then select the database which you want to access. In our case, we are going to use RDDEVDB. After clicking on the database that is going to be used, you’ll notice in the lower left-hand side there is a Resources section. To the right of this section is another link of the database name. Select the database name to view the Database Details. After clicking on the database name, you will be on the Database Details page. This great if we wan to get the Container Database information; however, we want to dive a bit deeper to the Pluggable Database. On the left-hand side, you’ll see the Resources section. Under this Resources section, notice that there is a link for Pluggable Databases. After clicking Pluggable Databases, the bottom of the Database Details page will change to show the Pluggable Database. Once this happens, you will see the name of the Pluggable Database that we want to connect to. Clicking on the Pluggable Database link, will bring you to the Pluggable Database Details page. On this page, there is a series of buttons at the top of the page. These buttons allow you to review a variety of items for the Pluggable Database. Where you are most interested in is the button that says “PDB Connection”. By clicking the “PDB Connection” button, opens the details we need to make a connection from the Bastion host. When reviewing the connection strings, it is best to use the “Long” version of the connection string. Within this connection string, you will want to use the “Host” information. The contents of the “Host” should be a private ip address on your VCN. In our case the IP address is 10.0.0.233 and listening on port 1521. Also make note of the service name for the PDB. This will be used later as well. Now that we have the connection information we need to connect to the Pluggable Database, lets take a look at how to build the Bastion Host. Building a Bastion Host The Bastion host is considered a security feature of the OCI framework. When looking for the Bastion configuration pages, it will be found under Identity & Security of the OCI pages. After accessing the Bastions page, there will be a “Create Bastion” button. This will open the dialog where you can name the Bastion host, provide the VNC and subnet, and what CIDER block can access the Bastion. In this example, I’m allowing access from anywhere by using a cider of 0.0.0.0/0. After filling in all the required information, click the Create button at the bottom of the dialog. This will kick off the creation process. Once the Bastion host is create, the Bastions page in OCI will show that the bastion host is active. With the Bastion host active, click on the name of the bastion to access the Details page. On the detail page, you can see the specific details of the host. On this page is a “Sessions” section where you can define the allowed sessions for connecting to the DBCS Pluggable database. Defining a Bastion Session When you are on the Bastion details page, a session can be created by clicking the “Create session” button. This action will bring up the dialog for creating a session. There are a few items that need to be either edited or selected on this page. Since we are going to connect to a DBCS instance, the session type should be “SSH port forwarding session”. Then provide a session name and select connect via IP address. Next provide the IP address which was identified earlier – which was 10.0.0.233. Change the port number from 22 to 1521. Lastly, select the RSA public key you want to use. In this case, I’m using a key that I previously created – id_rsa1.pub. If you click the link at the bottom for “Show Advanced options”, you will get the maximum time-to-live settings. One-hundred and eighty (180) minutes is the max that can be set. If you try to add anything higher, the create session process will error out. After setting all this information, click the “Create session” at the bottom of the dialog. At his point, the Bastion detail page will be updated and it make take up to a minute for the session that was created to show active. Database Connection through Bastion Host Up to this point, this blog has been about identifying the needed information for the database that we need to connect to as well as setting up the Bastion host. With both of these items out of the way, now we can establish a connect to the database. In order to make a connection to the database, we have to first open the SSH tunnel needed. Open an SSH tunnel With the Bastion host created and the session for connecting to the a database on port 1521 running, we now have to open the tunnel. In order do this, we have to first find the SSH command to run. This can be viewed by selecting the three vertical dots at the end of the session table. There is an option for “Show SSH command”. When this is selected, a dialog will appear showing the command for establishing an SSH tunnel through the bastion host. This command needs to be copied and then pasted into a command line terminal. The items enclosed in <> need to be updated. These items should point to the matching private RSA key and the local port mapping that will be used to connect to the database – in this case it will be 1521. ssh -i -N -L :10.0.0.233:1521 -p 22 ocid1.bastionsession.oc1.iad.********************************************************************************bxq@host.bastion.us-ashburn-1.oci.oraclecloud.com Update to ssh -i /Users/bcurtis/.ssh/id_rsa1 -N -L 1521:10.0.0.233:1521 -p 22 ocid1.bastionsession.oc1.iad.********************************************************************************bxq@host.bastion.us-ashburn-1.oci.oraclecloud.com If the RSA key requires a password, it will prompt for it. After providing the password, the tunnel will be established. It will be hard to tell, but after the password is entered and the return key struck the tunnel will be intialized and no command prompt will be returned – as illustrated in the below image. Make Database connection With the SSH tunnel established, we can now make a connection to the Oracle database with OCI. Using a sql tool like SQL Developer, we can quickly test a connection and then make a connection. From SQL Developer, open the New/Select Database Connection dialog box. From here, we will provide the details needed for connecting to the Pluggable Database – information gathered earlier in the post. With all the required information filled out, select the “Test” button at the bottom to confirm a successful connection. At this point, the connection to the Pluggable database can be established by clicking the “Connect” button. As you can tell, we have successfully connected to the OCI DBCS Pluggable Database this is on the private network within OCI. This is established through the Bastion host that was configured and accessible from anywhere.", "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" : "Access Oracle DBCS Pluggable Database via Bastion Connection", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/title_image_bastion_1-1024x876-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/access-oracle-dbcs-pluggable-database-via-bastion-connection", "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" : "Something that has been brewing for years – since late 2017 – is the constant request from Oracle customers on how to capture data from PostgreSQL databases. Many of Oracle’s customers are either moving towards PostgreSQL and off of Oracle or looking for another way to pull data from PostgreSQL into their Oracle Data Warehouses. In either case, Oracle has finally gotten around to releasing a fully supported version of Oracle GoldenGate for PostgreSQL, meaning that customers can now capture (extract) and apply (replicat) data from PostgreSQL 10 and later. The downside to this is that Oracle released it in “Classic” architecture instead of the “Microservices” architecture. Meaning customers still do not have access to remote administration capabilities and will have to rely on server access. A positive though is that this version of Oracle GoldenGate can be used in a hub-n-spoke architecture and for bi-directional replication. I will not be covering those topics though. Let’s get started … Prerequisites: As with anything there is always a set of prerequisites that are needed before you can proceed with an installation. In this cases, it holds true – the Oracle docs don’t even cover a good bit of these, but with a little help I was able to resolve what was needed. Linux Packages: PostgreSQL#-contrib – this package is needed to allow you to register the extract with the PostgreSQL database PostgreSQL.conf file changes: These items were interesting and documented in Oracle docs, but remember, after changes the PostgreSQL database must be restarted. wal_level = logicial max_replication_slots = 10 (default) max_wal_sender = 10 (default) wal_receiver_status_interval (optional) wal_sender_timeout (optional) track_commit_timestamp = false (optional) As you can tell Oracle is leveraging the Write Ahead Logging (WAL) parameters to ensure everything is read from the database and transaction logs correctly. Users: Just like typical Oracle GoldenGate setup, you must define a user that will be used for Oracle GoldenGate. In my setups, I typically name the user “ggate” but this user can be named anything. The key here is to ensure the right privileges are assigned. To setup an Oracle GoldenGate user, the following can be ran against a PostgreSQL database: create user ggate with password 'ggate' login; alter user ggate with replication; Environment Variables: There are a slew of environment variables that will need to be set to ensure that replication works. What is listed below is what I had to setup to ensure it all worked. Mileage will vary. export PG_HOME=/usr/pgsql-12 export OGG_HOME=/opt/app/oracle/19.1.0/oggcore_1 export ODBCINI=/home/oracle/odbc.ini export LD_LIBRARY_PATH=$PG_HOME/lib:$OGG_HOME/lib:$LD_LIBRARY_PATH export PATH=$ODBCINI:$PATH A couple of things to note here. The $PG_HOME must be in the $LD_LIBRARY_PATH. The $ODBCINI file location must be in the $PATH. These items can be easily setup in the .bashrc or .bash_profile for your environment. ODBC.ini file: Oracle GoldenGate uses the ODBC.ini file to connect to the PostgreSQL database. This file has to be configured and located by using the $ODBCINI environment variable. For simplicity of this blog, a little, I’m not going to post what it should look like. You can fine details within the Oracle docs -> here. Setting up replication: With all the prerequisites established, replication can be setup the exact same as any other Oracle GoldenGate “Classic” environment. The steps are similar to these below. Extract: 1. Install Oracle GoldenGate software – unzip/untar in the $OGG_HOME of choice. Then open GGSCI and run CREATE SUBDIRS (./GGSCI) + (CREATE SUBDIRS) 2. Edit the MGR parameter file (EDIT PARAMS MGR), assign port number (default 7809), and start manager (START MGR) 3. Login to the PostgreSQL databases as your GoldenGate user (DBLOGIN SOURCEDB USERID PASSWORD ) 4. Register extract with PostgreSQL database (REGISTER EXTRACT ) 5. Add extract (ADD EXTRACT , TRANLOG, BEGIN NOW) 6. Add trail file (ADD EXTTRAIL ./dirdat/aa, EXTRACT ) 7. Edit parameter file for extract (EDIT PARAMS ) 8. Add Trandata (ADD TRANDATA .) 10. Validate that MGR and EXTRACT have been started (INFO ALL) Replicat: 1. Create the GoldenGate schema inside of the PostgreSQL database (CREATE SCHEMA ) 2. Login to the PostgreSQL database (DBLOGIN SOURCEDB USERID PASSWORD ) 3. Add Checkpoint Table (ADD CHECKPOINTTABLE .) 4. Add Replicat (ADD REPLICAT , EXTTRAIL ./dirdat/aa, CHECKPOINTTABLE .) 5. Start Replicat (START REPLICAT ) 6. Check status of Replicat (INFO ALL) What you didn’t see/Summary: In the examples above, what was missing is the Data Pump Extract. Since I was configuring the movement of data on a single server with a single PostgreSQL database to two (2) different schemas, the Data Pump Extract was not needed. If you plan on moving data between sites, the Data Pump Extract is needed to route the trail files correctly. Another option is to configure Oracle GoldenGate in the hub-n-spoke architecture and the same approach as above can be followed and simply use the remote-capture/remote-apply functionality. In closing, Oracle has finally answered the call from customers by allowing them to capture and apply within a PostgreSQL environment. This brings the replication standard of reliable replication to a development platform as well as enabling organizations to maximize their data movement strategies. Enjoy!!) 9. Start MGR and EXTRACT (START MGR) + (START EXTRACT", "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" : "Replicating PostgreSQL data using 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/replicating-postgresql-data-using-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" : "Data ingestion is always the beginning stages of getting data into a data warehouse and/or cloud. Recently, we had the opportunity to design, build, and implement a data ingestion solution using Oracle GoldenGate Service (GGS) within Oracle Cloud Infrastructure (OCI). Within the a cloud-to-cloud environment, we were able to ingest 2.9TB of data between 10 to 14 hours compared to a two week proof-of-concept, that was performed by another vendor. This is a huge savings of time and provided our customer, with a Return On Time (ROT) between 95% to 97% – allowing them more time for their DBAs to focus on tasks. In this white paper, you can get a sense of the high-level items that it took to achieve this type of return. Although this was done within a single cloud and between two tenancies, these approaches can be used on-premises, on-premises-to-cloud, and cloud-to-cloud. Where we can help? RheoData are the experts in helping organizations move mission critical database workloads between on-premises resources to the cloud! Wether your organization is considering moving on-premises to on-premises or looking to do a lift-n-shift to the cloud, maintaining operational readiness is the key to a successfully migration! RheoData experts can help you evaluate, plan, and implement a data integration/migration strategy to successfully build for the future! Get in touch today to build your migration strategy! —> sales@rheodata.com", "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" : "Hyper Data Ingestion with Oracle GoldenGate Service (GGS)", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/HyperDataIngestion1-2-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/hyper-data-ingestion-with-oracle-goldengate-service-ggs", "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" : "Recently we have been talking with customers about their Oracle GoldenGate implementations and how these implementations can benefit their enterprise architecture. During these discussions, one thing that sticks out is the need for performance, performance tuning, and how that actually correlates to what is happening in the database. There seems to be a bit of misunderstanding when it comes to this topic. Let’s try and explain that here! Over the years, we have looked into this topic multiple times and have concluded that Oracle GoldenGate performance is directly tied to the performance of the database which it runs against. At the same time, there are settings that can be adjusted at the Oracle GoldenGate layer to help improve performance based on the data and how that data is to be captured and applied. In giving this some thought, we have come up with a simple yet interesting formula that helps explain how Oracle GoldenGate can help organizations capitalize on their investment of this “plumbing” product. The basis of the formula is Time. Basically, how much data can be captured/applied in the smallest amount of time? In general, Oracle GoldenGate does a “capture” of the data from a source data store and then “applies” this data to a target data store. Depending on the flavor of Oracle GoldenGate the information that is captured is either general information from the redo logs (checkpoint markers) or SQL statements from the transaction logs (older versions of Oracle GoldenGate will also pull the SQL statements). The speed at which this “capture” and “apply” process is done plus the time the database has to wait for access for data will be the determining factoring of how much time it takes to move data. Remember, that Oracle GoldenGate operates on commits. A commit has to happen before data is actually moved. Meaning, the amount of time it takes to commit on both sides has a direct correlation to performance. To illustrate, a basic understanding of how Oracle GoldenGate works is needed. The general flow of how Oracle GoldenGate works is illustrated in the image below: An extract will capture data from either the online redo logs or a transaction log when a commit happens. Then the transaction is retained in a trail file, shipped across the network, and then read and applied on the target. Where the replicat will acknowledge the apply when a commit is processed. To dive a bit deeper and further understand how this is related to performance, a detail review of the Integrated Extract and Intergrated Replicat are below. The Integrated processes are used for the Oracle platform. For heterogenous platforms, similar concepts are used, but not exact. Extract The “capture” process is also know as an Extract. For many Oracle implementations, a single extract is all that is needed to pull high volumes of data. The extract process, within an Oracle context, is pretty efficient. Oracle never releases benchmark numbers and this is why people think they may need more than one extract. The only time you need more than one extract is when you want to break up schemas for business reasons. As already mentioned, a single Integrated Extract will perform well in most use-cases. Starting with Oracle GoldenGate 18c (for Oracle), what is termed as “Classic Extract” has been deprecated and removed as of Oracle GoldenGate 21c. For other versions of Oracle GoldenGate (for non-Oracle, Big Data, and Mainframe), the “Classic Extract” still exists. This means for all Oracle implemenations, the “Integrated Extract” has to be used. By using the “Integrated Extract”, you are directly tieing the capture processes to the Oracle Database and the LogMiner process. Resulting in all transactions being pulled from the online redo logs, unless a checkpoint is found back in the archive logs. In that case, the extract will mine the archive logs and catch up to where it needs to in the redo logs. The Integrated Extract is built to be efficient and ensure transactions are captured in transactional order. The internals of the Integrated Extract can be conceptualized in the below image: The breakdown of the Extract is as follows (left to right): Reader – Reads logfile/redo logs and splits transactions into regions Preparer – Scans regions of logfiles/redo logs and pre-filters based on parameters Builder – Merges prepared records in System Change Number (SCN) order Capture – Formats Logical Change Record (LCR) and passes to GG Extract Once a commit is performed in the Oracle Database, the transactions are read from the online redo logs, prepared, built in transactional order, then actually captured. Once “captured”, the transactions are stored in the trail file. At this point the trail file is shipped across the network to the target location. With the integrated extract being pretty efficient, how can we gage or increase performance of the process? Extract Performance For an extract to perform as expected, the Oracle Database needs to be configured to support the integrated process. This means that items like memory and waits need to be address. The first areas that need to be tuned are memory related: Memory (Oracle related) The memory that the integrated extract requires is tied into the System Global Area (SGA). Each extract that is configured against an Oracle Database requires 1.25G of memory in the Streams Pool (stream_pool_size). This setting is often over looked and customers think they need more than one extract. At the same time, if you need more than one extract, you’ll have to allocate 1.25G of memory per extract. Waits (Oracle related) Waits are a different aspect of Oracle GoldenGate performance. Oracle GoldenGate operates on the premises of commit-to-commit. Meaning, any transaction that is open and not committed will not be replicated. This type of issue is typically seen in developers leaving transactions open and walking away or batch process trying to process large amounts of data without a commit. Both lead to possible wait issues. At the same time, commits can cause issues with waits as well. If a system is configured with control files on different I/O locations (non-ASM), “concurrency” waits can cause huge spikes in performance issues with Oracle GoldenGate. The way to remedy this is to ensure that the application or batch processes are committing frequently. Extract Recommendations For extracts, our recommendations are the following: For each extract, allocate a minimum of 1.5G of memory in the Streams Pool Ensure that applications are committing frequently, based on application needs If using batch processing, increase the frequency of committing Replicat On the other side of the configuration is the replicat. Replicats are used to apply the transactions in a transactional order. Depending on the volume of data, there are different types of replicats that can be used. In total there are five different replicats: Classic Replicat Coordinated Replicat Integrated Replicat Non-Integrated Parallel Replicat Integrated Parallel Replicat Each version of the replicat has it benefits and use-case which it can be leveraged for. In newer implementations of Oracle GoldenGate, it is recommended to use a Parallel Replicat. For practical purposes with Oracle Database, the Integrated Replicat should be used. The other versions of the replicat should be used on a case-by-case determined by the volume of data being processed. The Replicat is actually made up of a few different components. These components are: Replicat (a lightweight streaming api) Inbound Server (multiple components) The Inbound Server is made up of four (4) different pieces that enable the apply process. The pieces are: Receiver – reads the logical change record (LCR) from the trail file Preparer – computes the dependancies between transactions (PK, FK, UK) Coordinator – maintains the order between transactions Apply – applies the transactions in order including conflict, detection, and resolution (CDR) and error handling Replicat Performance Similar to the extract process, the performance of the replicat relies on the performance of the database. This means items like memory and waits can have an affect on the performance. The first area that needs to be addressed for performance tuning is memory. Memory (Oracle related) The memory that an integrated replicat requires is tied to the System Global Area (SGA). With each integrated replicat configured against an Oracle Database, the process requires 1.25G of memory in the Streams Pool (stream_pool_size). This allows the for the transactions to be funneled into the streaming api and cached. Then the receiver process can read the LCRs quickly, enabling the preparer and coordinator to put the transactions in order. Once the transactions are in order, the apply process can apply the transactions to the database. If needed the apply process can be scaled based on the parallelism settings in the database. All this is coordinated and done within the memory allocation defined with the SGA and streams pool. Waits (Oracle related) Similar to the extract process, waits within the Oracle Database can have an impact on the performance of Oracle GoldenGate. The biggest concern that can cause a wait for Oracle GoldenGate is the timing on which commits happen. If a commit is not happening frequently, then the corresponding lag will increase. Similar if a commit is happening so soon, lag will not show any performance issue but you may get concurrency waits due to control file writes. The commit frequency of the the application, by business defitions, will have a direct impact on the performance of both the Oracle Database and Oracle GoldenGate. GoldenGate Parameters There are a few Oracle GoldenGate parameters that can help with either identifying performance related issues or ensure a level of performance within the replication stream. These parameters have been broken down into they processes that they support. Extract Parameters LOGALLSUPCOLS – instructs the extract to write all supplemental log columns to the trail file UPDATERECORDFORMAT – writes a single LCR that contains both the before and after images of the transaction. Setting this to COMPACT will reduce the amount of data in the trail file. PARALLELISM – controls the number of prepares that are used to process online redo logs. MAX_SGA_SIZE – controls the amount of memory configured per extract. Typically set to 1.5G per process Replicat Parameters COMMIT_SERIALIZATION – used to define how transactions are ordered. Default is DEPENDENT_TRANSACTIONS. Set to FULL if needing source commit order. EAGER_SIZE – Threshold to begin applying large transactions (9500 (default)). Serializes apply process. MAX_SGA_SIZE – controls memory resources for Integrated Replicat. Defaults to INFINTE PARALLELISM – controls number of appliers (defaultL 4) MAX_PARALLELISM – controls max number of appliers. Note: MAX_PARALLELISM = PARALLELISM, disables auto tuning of replicat Results By understanding what the Integrated Extract and the Integrated Replcat processes do, we can quickly identify ways to increase performance. Using the basic information outlined, we were able to product a 94% increase in performance on small Dell T110 (i3) machines. This was a remarkable increase in performance per minute. If you are looking for more information on how to turn your Oracle GoldenGate or Oracle Database; contact us at hello@rheodata.com.", "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" : "Performance with Oracle GoldenGate", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/gg_performance-scaled-1.jpg", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/performance-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" : "Businesses are constantly finding themselves increasingly reliant on data ingestion, big data, analytics, and following traditional ETL (Extract, Transform, Load) processes; which at times can be a bottleneck to timely business functions. At AWS re:Invent 2023, Amazon recognized this and announced the concept of Zero-ETL. Other companies, such as Snowflake and Salesforce followed suite by launching features that further modernized data integration. In doing research on Zero-ETL and closer scrutiny, the concept of Zero-ETL is more aligned with ‘zero integration’ rather than the removal of ETL from business processes. So what is Zero-ETL? Zero-ETL is a type of data integration that doesn’t involve the use of traditional approaches of extract, transform, and load (ETL). Unlike traditional methods that involve ETL and loading data between systems, Zero-ETL moves data directly from one system to another. It is a a no-frills approach to data transfer, eliminating any need for intermediate steps to clean or modify the data. In essence Zero-ETL is data replication, ensuring almost instant data transfer without the processing hurdles. Zero-ETL is becoming popular? The concept of Zero-ETL has become popular in the data management domain, in part, by the prevailing belief that it acts as a potential substitute for traditional ETL. This perspective have organizations and industries, leading many to consider Zero-ETL as the “next step” or even a “replacement” for ETL. Traditional ETL processes, with their structured approach to ETL (extracting, transforming, and loading), have been foundational in data integration for decades. ETL enabled businesses to harmonize diverse data sources, making them ready for deeper analytical tasks, AI modeling, and ML implementations. With the introduction of zero ETL and its focus on direct data transfers, there’s a new narrative – emphasizing immediate, transformation-free data transfers. This narrative is attractive to many, especially those looking for simpler and quicker data replication solutions. Is the nomenclature of Zero-ETL misleading? With the nomenclature of Zero-ETL, the marketing term is catchy and can quickly lead to discussions; however, this is also a point of contention. The term “Zero-ETL” is more like “Zero-EL.” The technology that embodies the concept of “Zero-EL” concentrates on the extraction and loading stages of the process while sidestepping the transformation step of the process. With the advancement of technologies, the trend of reducing unnecessary data movement is becoming apparent; however, data movement is still required! The technologies and procedures for extracting and loading data are ever evolving and becoming more simplified; but the transformative aspects remain a significant part of the puzzle before the industry can truly embrace “Zero-ETL”. Transformative processes are integral to shaping and repurposing data for operational and analytical needs. Benefits of Zero-ETL: Let’s put aside the catchy marketing terms like “Zero-ETL” for the next few minutes. There is no doubt that the industry is looking for simpler, easier, and efficient way of data movement and data management; there are an array of benefits: Speedy Data Transfer – Promptness of data transfers. Emphasis on direct data movement allows for swift data migrations. This facilitates timely insights and promotes swift decision-making. Simplified Implementation – Leads to quicker setups, minimizes learning curve, and simplified maintenance; enabling a smoother process for integrating new data sources. Cost Efficiency – Capitalize on cloud-native platforms and scalable data integration technologies; leading to cost-effective solution. Enhanced Data Quality – the directness of Zero-ETL can lead to more transparent data transfers. When preserving data integrity is crucial, the direct approach can provide a higher assurance of quality; ensuring data remains consistent and reliable. Real-Time Insights – data is often available in real-time or near-real-time as long as the data needs little transformation, no cleansing, or augmentation. The prompt availability of data can yield more accurate analytics, optimized AL/ML trianing, and ensuring up-to-date reporting. In summary of these benefits, Zero-ETL is rooted in these benefits with an emphasis on immediate data replication. Disadvantages of Zero-ETL: With every new solution, marketing catch phrase, or technology, there is always drawbacks. Zero-ETL is an exciting “concept” and is making a lot of noise in the data community with data engineers and others; yet it is worth looking at some of the disadvantages of this concept. Limited Data Transfer Capabilities – data movement between systems sometime requires intermediate steps; this presents challenges when data requires cleaning, standardization, or complex transformations prior to consumption. Hindering the ability to cater to most data reporting needs. Compromised Data Governance – traditionally, ETL solutions are equipped with controls to safeguard and uphold the quality of the data transfers. Zero-ETL leans on the systems that are involved in the transfer to manage the critical tasks. Restricted Integration Potential – the Zero-ETL concept is characterized by its direct data transfer between systems; which can be a limiting factor when the systems involved are outside of the particular ecosystem. This confinement can restirict the integration mechanism, potentialy leaving out valuable data sources. When could Zero-ETL be the right approach? Like all technologies and concepts that come to market, the efficacy of Zero-ETL hinges on understand the benefits and disadvantages. The two concepts, where organizations and industries could leverage Zero-ETL are: Instant Replication: Scenario: Organizations resort to defined ETL solutions to transfer data from transactional databases to a central data repository. Zero-ETL Application: Zero-ETL can function as a data replication instrument, enabling Change-Data-Capture (CDC) techinques to directly mirror data into a data warehouse. Streaming Ingestion: Scenario: Organization relies on real-time data inputs from a myriad of sources. Data must be immediatly accessible for analytics purpose without intermediate storage or transformation. Zero-ETL Application: Data streaming and message queuing platforms channel real-time data. Integrating Zero-ETL methodology with a data warehouse, data from input streams become immediately available for analytics Where or what tools does Oracle offer that support Zero-ETL? In the Oracle eco-system, the underlying concepts of Zero-ETL have always existed within Oracle Data Integration stack. Over time, the associated data integration stack has changed between on-premise and cloud; and the terms that Oracle use are around “data mesh” and many other terms. The Oracle products that can help organizations enable the concept of Zero-ETL are: On-premises: Oracle GoldenGate (all versions and free) Oracle Data Integrator (ODI) Oracle Database (converge database) Cloud: Oracle GoldenGate Service (GGS) Oracle Autonomous Database (ADW/ATP/AJD) Oracle MySQL Heatwave (OLTP and OLAP in same database) Conclusion: New terms and technologies emerge on a regular basis and capture the attention of decision-makers and practitioners alike. With all trends, it is critical to evaluate each trend before diving in. Understanding the core functionality, strengths, and limitation of the tools that enable Zero-ETL is vital. Every tool and technique has its place, the key to discerning is how, when, and where to apply them the best. Don’t always buy into the hype and find more of a fit for the concept and use the correct technologies.", "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" : "Zero-ETL: What is it and what Oracle products support it", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/zero-etl-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/zero-etl", "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" : "Recently I’ve been playing with Oracle’s MySQL Database Service (MDS) and testing out the Heatwave option. Heatwave is very impressive and enables MySQL to run OLAP workloads within a smaller database on the Oracle Cloud Infrastructure (OCI). Within the MySQL Database Service there are only a few compute shapes that support the option for Heatwave. These shapes are: MySQL.HeatWave.VM.Standard.E3 MySQL.HeatWave.BM.Standard.E3 Both shapes support the usage of HeatWave clusters. At the same time, you can see that there are only a few shapes that support the use of offloading queries. Although this is not the point of this post, it is good to keep this in mind. Not every shape will support the HeatWare api. Once a MySQL Database Service (MDS) with HeatWave is running, queries can be offloaded. There may be times when you don’t want to use the HeatWave option after it was enabled, yet the MDS System Details page doesn’t show an option to remove HeatWave. Leaving the question of how to remove HeatWave from the MDS if it is not needed? To remove HeatWave from an MySQL Database Services, do the following: Validate that the MDS is configured with HeatWave. This is done from the MDS DB System Details page. Notice that the area highlighted only shows that HeatWave is enabled. It also shows you that it is using two nodes with a memory capacity of one terabyte. To remove HeatWave, you have to go to the bottom of the page, on the left hand side under the Resources section. Under Resources, you will see an option for HeatWave. By clicking the HeatWave option under Resources, opens up the sub-page that provides details on HeatWave itself. From here, you can see the size of the HeatWave cluster, Shape, status among the nodes that has been built. At the same time, there are buttons for edit, start, stop and restart. At the same time there is a big read delete button! When you select the big red delete button, it will prompt you to confirm that you want to delete the HeatWave cluster. By clicking the “Delete HeatWave Cluster” (big red button), this will remove all the HeatWave nodes in the cluster. After confirming that you want to remove the Heatwave Cluster, the Resource section will update with a status of “Deleting” Once the delete process is done, your MySQL Database System is returned back to just a normal MDS configuration and HeatWave is disabled. Oracle has made it very easy to take an existing MySQL Database Service (MDS) and plugin a HeatWave cluster. At the same time, they made it easy to remove when you don’t need the extra processing power for queries. Enjoy!!!", "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" : "Removing a MySQL Heatwave Cluster", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/mds_heatwave_enabled-3.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/removing-a-mysql-heatwave-cluster", "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" : "This is just a quick reminder post to illustrate how to stop all docker containers that are running within a given environment. As many may already know, you can use the standard Docker stop command to stop a given container. What if you want to stop all containers within your development environment? The simple way is to combine Docker commands. The first command that is useful is to find out what is running. In this case, the command is: docker pa -a This command will return a list of all the containers that are present on the system – running or exited. What you want to get at this point is the “CONTAINER ID”. If you add in the -q option, the resulting return set will only display the “CONTAINER ID” that are needed. bocurtis@MacBook-Pro ~ % docker container stop $(docker ps -a -q) 8389aff2f804 64718fec99f4 b8d66e2701e2 4bd42b951052 b5e1edc7ef1f The next command that is needed is the stop command. This command is the command that will actually stop all the containers that is it passed. Typically this would be one-by-one, but you are trying to stop all of them at one time. To do this, you simply pass the docker ps command to the container stop command like so: docker container stop $(docker ps -a -q) At this point, you can perform a process (ps -a) command and see that everything has been stopped. Hope the helps and is a quick reference to stopping more than one container. 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" : "A simple way to stop all Docker containers", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-59-35-1982-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/a-simple-way-to-stop-all-docker-containers", "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" } } ```