--- title: RheoData Blog | goldengate 19c description: goldengate 19c | 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) - 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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 # goldengate 19c ## [Basic DDL Replication with Oracle GoldenGate](https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate) Posted by [Fame](https://rheodata.com/en-us/blog/author/fame) | Nov 10, 2025, 9:31:00 PM With any type of replication configuration or replication tool, primary purpose is to move the data... [CONTINUE READING](https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate) ## [RheoData achieves Service Expertise in Oracle GoldenGate](https://rheodata.com/en-us/blog/rheodata-achieves-service-expertise-in-oracle-goldengate) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025, 9:30:56 PM Three and a half-years after our owner/founder left Oracle; RheoData has earned the Oracle Service... [CONTINUE READING](https://rheodata.com/en-us/blog/rheodata-achieves-service-expertise-in-oracle-goldengate) ## [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) ## [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) ## [GoldenGate Parameter Files – Format and Logic](https://rheodata.com/en-us/blog/goldengate-parameter-files-format-and-logic) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025, 9:30:02 PM As we have done multiple engagements with Oracle GoldenGate and helped clients get the most out of... [CONTINUE READING](https://rheodata.com/en-us/blog/goldengate-parameter-files-format-and-logic) ## [Manually purging trail files from OCI GoldenGate Service](https://rheodata.com/en-us/blog/manually-purging-trail-files-from-oci-goldengate-service) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025, 9:29:24 PM Oracle GoldenGate Service is Oracle’s cloud offering to quickly use GoldenGate to move data within... 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[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" : "goldengate 19c | 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/goldengate-19c", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://rheodata.com/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "With any type of replication configuration or replication tool, primary purpose is to move the data as transactions are committed between databases. Any of the tools on the market are great for replicating data, but where replication starts to become interesting is when the metadata for tables needs to be replicated. When something changes at the data definition layer occur, these changes have be shipped across the network. Replication tools need to be able to handle the capture, shipping, and applying of an object’s data definition language (DDL). With Oracle GoldenGate, improvements have occurred over the years to make replicating DDL easier. Although, replicating DDLs have become easier there are items that need to be considered. In this post, we’ll look at these common items. Overview of DDL Synchronization Oracle GoldenGate supports the synchronization of DDL operations from one database to another. DDL synchronization can be active when: Business applications are actively accessing and updating the source and target objects Oracle GoldenGate transactional data synchronization is active (DML) The components that support the replication of DDL and replication of transactional data changes (DML) are independent of each other. Therefore, you can synchronize: Just DDL changes Just DML changes Both DML and DDL This means that Oracle GoldenGate can perform both DML and DDL at the same time or independent of each other. This provides flexibility to the overall architecture and allows the administrators the option to define what needs to be replicated and when. Fetch-Related Inconsistencies With everything being flexible and easy to replicate, there is a defined process to ensure that inconsistencies are minimized when DML and DDL are fetched. For example, the following process will help prevent fetch-related inconsistencies while Oracle table columns are being modified: Pause all DML on table (i.e. stop any process that is processing inserts, update, or deletes) Wait for the Extract to finish capturing all remaining redo; wait for Replicat to finish processing all captured data in trail. Execute the DDL on source; confirm DDL changes on target Resume source DML on table Enabling DDL Replication DDL is useful in dynamic environments which change constantly. By default, the status of DDL replication supports the following: On source (Extract), the Oracle GoldenGate DDL support is disabled by default. Must be configured with the DDL parameter. On target (Replicat), DDL support is enabled by default, to maintain the integrity of transactional data that is replicated. DDL Parameter (Extract/Replicat) The DDL parameter can be used in both the Extract and Replicat parameter files. By using DDL parameter in the Extract is will enable DDL capture. It can be omitted from the Replicat parameter since DDL is enabled on the target side by default. Sample Parameter Files Extract: extract EXT useridalias SOURCE domain OracleGoldenGate exttrail aa ddl sourcecatalog chip table tstusr.random_lrg_; Replicat: replicat REP useridalias PDBSOURCE domain OracleGoldenGate ddl map chip.tstusr.random_lrg_, target chip.tstusr1.random_lrg; Hopefully, this quick post shows you how easy it is to get DDL enabled within Oracle GoldenGate. Enjoy!!", "author" : { "@type" : "Person", "name" : "Fame", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/fame" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Basic DDL Replication with Oracle GoldenGate", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/basic-ddl-replication-with-oracle-goldengate", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Three and a half-years after our owner/founder left Oracle; RheoData has earned the Oracle Service Expertise in North America for Oracle GoldenGate. The accreditation was awarded in North American but we continue support you around the globe. RheoData is now positioned to bring quality Oracle GoldenGate on-premise and cloud services and licenses to our customers. GoldenGate Services we offer: Architecture review and health-checks Design and/or re-architect Health-checks on database and replication Migrate to the cloud (AWS, Azure, GCP with on-premise/OCI with BYOL or Cloud-base licenses) Oracle GoldenGate Implementation Oracle GoldenGate for Oracle Non-Oracle (Heterogenous) Big Data Oracle GoldenGate Managed Services Keep your environment running at peak performance – on-premise or cloud without the OpEX overhead Oracle GoldenGate Modernization Upgrade from Classic to Microservices Understanding of Microservices We help our customers achieve maximum performance with Oracle GoldenGate, on-premise and cloud while enabling their data to move in real-time at breakneck speed. RheoData has deep experience moving from Classic to Microservices architecture with virtually no interruption to ongoing operations. Here are a few of our use cases and customer success stores illustrating our capabilities: Shoe Carnival – Zero-downtime migration from Oracle GoldenGate (Classic) to Oracle GoldenGate (Microservices) (here) Altec – Hyber Data Ingrestion – OCI and GGS use case (here) Tire Manufacture Distributor – Oracle GoldenGate for Big Data to Google Cloud Storage (here) Migrate data to ADW – Oracle GoldenGate to Autonomous Data Warehouse (here) Additional GoldenGate consulting services aligned with our expertise, including: Data Integration, Consolidation, and Data Warehousing Query offloading for Reporting processes Bi-Directional/Multi-Master replication for high-volume transaction architectures Disaster Recovery Testing Real-Time Data Replication Big Data integration using Oracle GoldenGate to AWS S3 Big Data integration using Oracle GoldenGate to Kafka Big Data integration using Oracle GoldenGate to Snowflake Big Data integration using Oracle GoldenGate to Google Cloud Storage Oracle to Oracle Replication Oracle to MySQL Replication Oracle to Postgres Replication Microsoft SQL Server to Oracle Replication Microsoft SQL Server to MySQL Replication PostgreSQL to Oracle Replication PostgreSQL to PostgreSQL Replication Cloud integration with Amazon AWS Cloud integration with Google Cloud (GCP) Cloud integration with Azure Cloud integration with Oracle Cloud Infrastructure (OCI) Oracle GoldenGate Service (OCI based Oracle GoldenGate) Replication integration with REST API framewor We look forward to connecting with you on all your project, infrastructure, and performance needs, especially Oracle GoldenGate! Contact us today email (hello@rheodata.com) or by phone at +1 (678) 608-1352 x 102 or 103. How can we be helpful today?", "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" : "RheoData achieves Service Expertise in Oracle GoldenGate", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/rheodata_GG-Service-Badge-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/rheodata-achieves-service-expertise-in-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" : "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" : "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" : "As we have done multiple engagements with Oracle GoldenGate and helped clients get the most out of their investment; we have realized that 90% of the parameter files we deal will are not structured in a way that makes sense. Traditionally, Oracle GoldenGate parameter files are text files that are read and loaded into memory for execution. The order in which these files are read have an impact on how Oracle GoldenGate will operate. In this post, we will highlight the basics of how a parameter file should be structured for readability as well as operational practicality. With newer versions of Oracle GoldenGate, there are two architectures – Classic and Microservices. Depending on the architecture you are using will determine the number of parameter files you have to review. For the purpose of this post, we will look at parameter files that are associated with the Microservices architecture; meaning only looking at the extract and replicat parameter files. Parameter File Formats Every parameter file starts off with the basic first line of either Extract or Replicat followed by the name of the process. After that many clients randomly throw parameters throughout the file, leading to either missing data or unexpected errors. As basic format of the parameter file, a skeleton key is below as an example. After reviewing this structure, we’ll show you some examples of do’s and don’ts. [EXTRACT || REPLICAT] [MACRO SETTINGS] [LOGIN SETTINGS] [MEMORY MANAGEMENT] [ENVIRONMENT SETTINGS] [REPORTING] [DDL] [DATABASE OPTIONS] [TRANSACTION LOG OPTIONS] [MISC.] [TABLE || MAP] The above skeleton key is designed to provide a guidance as to how the parameter file should be laid out. Not all categories will be used in all parameter file; please use it as a guide to write better parameter files. Capture Process With in Oracle GoldenGate the capture process is also know as the Extract. The extract comes in two vesions – Non-Integrated and Integrated. In both cases, a single parameter file is used. At the same time, many clients get the formatting of a parameter file crossed up. In this example, everything is set at random in the file. There is no logic or reason for where items are placed. The end goal is to have a working extract. At the same time, if you take the stand point of the parameter file is read from top-down, then items are being set before they need to be. Although this parameter file works, it is messy and difficult to follow what is going on. Note: Values of the parameter file has been modified to protect the client Extract Bad Format: EXTRACT DBOPTIONS ALLOWUNUSEDCOLUMN DBOPTIONS LOBBUFSIZE 2097152 USERID ggate@, PASSWORD SETENV (ORACLE_HOME=“$ORACLE_HOME) SETENV (ORACLE_SID=“$ORACLE_SID) LOGALLSUPCOLS UPDATERECORDFORMAT COMPACT TRANLOGOPTIONS MININGUSER ggate@, MININGPASSWORD TRANLOGOPTIONS INTEGRATEDPARAMS (max_sga_size 2048,parallelism 4, downstream_real_time_mine Y) TRANLOGOPTIONS BUFSIZE 4096000 TRANLOGOPTIONS EXCLUDEUSERID 9 CACHEMGR CACHESIZE 16GB, CACHEDIRECTORY /gg/dirtmp 300GB RMTHOST , MGRPORT 7809 WARNLONGTRANS 2h, CHECKINTERVAL 10m TABLEEXCLUDE MIP.TPC_EN* TABLEEXCLUDE MIP.SIB* TABLE MIP.*; When we run this through the skeleton key format that is provided above it becomes a lot easier to read and work with. Extract Skeleton Format: EXTRACT USERID ggate@, PASSWORD --CACHEMGR CACHESIZE 16GB, CACHEDIRECTORY /gg/dirtmp 300GB SETENV (ORACLE_HOME=“$ORACLE_HOME) SETENV (ORACLE_SID=“$ORACLE_SID) WARNLONGTRANS 2h, CHECKINTERVAL 10m DBOPTIONS ALLOWUNUSEDCOLUMN DBOPTIONS LOBBUFSIZE 2097152 TRANLOGOPTIONS MININGUSER ggate@, MININGPASSWORD TRANLOGOPTIONS INTEGRATEDPARAMS (max_sga_size 2048,parallelism 4, downstream_real_time_mine Y) TRANLOGOPTIONS BUFSIZE 4096000 TRANLOGOPTIONS EXCLUDEUSERID 9 LOGALLSUPCOLS UPDATERECORDFORMAT COMPACT TABLEEXCLUDE MIP.TPC_EN* TABLEEXCLUDE MIP.SIB* TABLE MIP.*; After rewriting the extract parameter file, you can quickly see items that should be removed or adjusted. Example of this is the setting for CACHEMGR. Although this parameter is correct from a syntax point-of-view, this setting is turned on by default with newer versions of Oracle GoldenGate. In the skeleton format above, notice that it is proceeded with a double dash. This means that the parameter has been commented out of parameter file and will not be ran upon starting up. After that you can quickly scan other parameters as needed to define what is going to happen. This same formatting can be used in other parameters files as well, especially the Apply process (i.e. Replicat). By using this organized flow to a parameter file, the Oracle GoldenGate Administrator or the DBA can quickly identify what is happening in the file or if anything has changed. The added bonus of this format is it can be used in all versions of Oracle GoldenGate – on-premises and cloud. If you need help with your Oracle GoldenGate implementation, feel free to drop us a line 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" : "GoldenGate Parameter Files – Format and Logic", "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/goldengate-parameter-files-format-and-logic", "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", "headline": "Manually purging trail files from OCI GoldenGate Service", "mainEntityOfPage": "https://rheodata.com/en-us/blog/manually-purging-trail-files-from-oci-goldengate-service", "datePublished": "10/11/2025", "dateModified": "10/11/2025", "articleBody": "Oracle GoldenGate Service is Oracle’s cloud offering to quickly use GoldenGate to move data within OCI as well as other clouds. Now network connection and bandwidth has a bit to do with the speed of data being processed, but it a quick service over all. One thing that any GoldenGate Administrator has to get use to is the lack of access to the underlying host where GoldenGate is running. As my friends, the PMs, have told me this is due to GoldenGate Service being a “SERVICE”. This basically means you do not need or will get access to the underlying filesystem of GGS. For many GoldenGate Administrators this will be frustrating from a troubleshooting aspect – How do you confirm or make sure that trail files are being written to or read from? Well, the answer is in OCI GoldenGate Service, but that is not the point of this post. The item that needs to be discussed is how to clean up trail files in GGS? Cleaning up trail files is important because they do take space and if you don’t have a task enabled to clean up trail files, then space will be consumed and eventually used up. How do you take care of this issue then manually? The answer is simple and what is built into Oracle GoldenGate and Oracle GoldenGate Service – REST APIs. To purge a single set of trail files (all trail files) that begin with a specific name, the below code can be used in Microsoft Visual Studio Code (VSCode). @url = ### POST /services/v2/commands/execute Authorization: Basic Z2dhZG1pbjphbHRlY0dHUE9DYWRtaW4yMyE Content-Type: text/plain { name: purge, purgeType: trails, trails: [ { name: “AL } ], useCheckpoints: false, keep: [ { type: min”, units: files”, value: 0 } ] } ### In the above example code, we are removing all the trail files that being with “AL”. If you want to remove more than one series of trail files, we can simply add more trail file names to the code as follows: @url = ### POST /services/v2/commands/execute Authorization: Basic Z2dhZG1pbjphbHRlY0dHUE9DYWRtaW4yMyE Content-Type: text/plain { name: purge, purgeType: trails, trails: [              {                 name: “AL”               },               {                  “name”:”AB”               } ], useCheckpoints: false, keep: [                {                   type: min”,                    units: files”,                    value: 0                }          ] } ### If you are curious how this would look in a written cURL command, the below would do the same thing: curl --request POST \ --url /services/v2/commands/execute \ --header 'authorization: Basic Z2dhZG1pbjphbHRlY0dHUE9DYWRtaW4yMyE' \ --header 'content-type: text/plain' \ --header 'user-agent: vscode-restclient' \ --data '{name: purge,purgeType: trails,trails: [{name: AL}],useCheckpoints: false,keep: [{type: min,units: files,value: 0}]}' Enjoy!", "image": { "@type": "ImageObject", "url": "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/curlogg-2.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Bobby Curtis", "url": "https://rheodata.com/en-us/blog/author/bobby-curtis", "sameAs": "" }, "publisher": { "@type": "Organization", "name": "RheoData", "url": "rheodata.com", "logo": { "@type": "ImageObject", "url": "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" } } } ```