The Ultimate Guide to SAP Change Data Capture (CDC)
Multiple point solutions exist on the market today that claim to help get your SAP data out of SAP. But how well do they complement your existing technology stack? Moving SAP data out of SAP isn’t a one-time ad hoc project. It’s a critical part of your organization’s AI and analytics strategy. Modern cloud data architectures and business requirements have raised today’s standards; data pipelines need to be compliant, scalable, and reliable as the data foundation to keep up with business needs.
Chances are you’ve encountered the term “Change Data Capture” or “CDC” for short when evaluating solutions on how to move large volumes of data with frequent changes such as SAP data. This goes beyond simple access to SAP data and into connecting SAP data to your entire organization. CDC data pipelines are the gold standard when it comes to moving data to your cloud data warehouse, lakehouse, or data repository to fuel agentic workflows. This guide covers CDC methods as it applies to moving data out of SAP environments. However, if you’re looking for a refresher on what CDC is and its benefits, The Business Case for Change Data Capture is a great starting point.
3 Reasons to Switch to SAP Change Data Capture (CDC) Today
If you’re reading this, you’re likely interested in learning what’s the best way to tap into and leverage your SAP data. The first step starts with accessing and extracting your SAP data. When it comes to SAP data extraction interfaces, the total cost of ownership (TCO) of developing an in-house solution is usually not economical due to unique complexities of SAP data involving: a variety of data interfaces, convoluted structures, and proprietary languages such as ABAP. Even if you find developers with deep SAP expertise, it’s usually not a budget-friendly path forward.
Point solutions and heavyweight suites exist on the market when it comes to SAP data extraction, however, both come with considerable caveats. Point solutions don’t scale well because of a lack of features such as limited data connectors. On the other hand, heavyweight suites aren’t vendor-agnostic creating deeper ecosystem lock-in which restricts flexibility. As well, not all data extraction methods are equal. Because the SAP ecosystem is complex and constantly evolving, some solutions still rely on legacy connectors that aren’t performant for large scale data replication or are no longer compliant with SAP’s latest license usage guidelines.
Here are 3 reasons why you should consider a modern, unified SAP data strategy that includes CDC to move your data.
Cost Savings and Faster Data Delivery
There’s a reason why organizations are still using Java Connectors (JCo) as part of their SAP data architecture. JCo has been around for the last two decades earning its reputation as tried and true. It’s a solid option for linking SAP to non-SAP systems. That said, your SAP data strategy for moving SAP data shouldn’t be solely based on JCo. JCo doesn’t scale well, since it’s not a comprehensive solution and requires a connection for each SAP data object. This translates into high costs for data pipeline management requiring multiple custom connectors, ABAP resourcing for development, and frequent maintenance for SAP data extraction.
This is where CDC technology comes in. CDC excels at moving data. CDC technology is commonly bundled within managed connectors. It includes incremental or delta loading which is efficient on resources such as network bandwidth, a top data extraction obstacle. As a result of switching to CDC, you can expect cost savings from offloading maintenance and development as well as accelerated time to value and data delivery for your SAP data.
Note: Managed connectors are most preferred since they’re plug-and-play when it comes to standing up data pipelines fast to move your data. Boomi Data Integration does exactly that with hundreds of managed connectors you can explore in the directory.
Harmonized Insights Across Your Entire Business
Getting data out of SAP is hard. That’s why some choose to leave their SAP data behind. While not ideal, it’s a justified business decision. However, SAP data shouldn’t remain a black box forever because that’s precisely how data siloes are formed. Since it’s not captured as part of the overall AI and analytics strategy, a portion of the business that relies on SAP will remain in the grey area.
Introducing CDC can help take the guesswork out of running the business. CDC data pipelines are designed to efficiently and reliably move SAP data to your cloud data warehouse or lakehouse. This means full visibility into the side of the business that runs on SAP. Additionally, it means taking full advantage of your data lakehouse by producing harmonized insights that could have been previously deprived of SAP data.
Getting Ahead of the Competition with SAP Agentic Workflows
95% of generative AI pilots at companies are failing to deliver ROI due to flawed integration1. In order to create agentic workflows that deliver value, organizations must have sturdy foundations in secure APIs, model context protocol (MCP), and of course trusted data.
The rationale behind using CDC for your SAP data is twofold. The first is getting your data out of SAP and the second is fueling SAP agentic workflows. Even if your SAP data is trusted, high-quality, and enterprise-ready, a CDC solution is necessary to ensure it gets moved expediently and reliably to where a SAP AI agent or agentic workflow will consume it. Otherwise, your SAP agentic workflow isn’t working with up-to-date or complete data. The low quality data input will hamper its effectiveness in executing SAP-related tasks. It’s as the old adage goes for any data related initiative: “garbage in, garbage out”. This is why it’s critical to have modern data pipelines with CDC that fuel your SAP agentic workflows properly.
Source: The GenAI Divide: State of AI in Business 2025 (MIT, 2025)
Fig. 1 – Example flow diagram using Boomi for SAP Data Connector to integrate SAP data
Overview of CDC Methods for SAP Data
As you upgrade your data foundations and venture into enterprise data pipelines, you’ll find
different types of CDC methods to support SAP data extraction. The CDC flow comes into effect after your initial data migration or extraction. With CDC enabled, you’ll be efficiently capturing any changes made to your SAP data without missing a beat. In this section, we’ll outline the common CDC methods and how each of them applies to SAP data extraction.
Note: The Business Case for Change Data Capture contains more details about each CDC method’s trade-offs, performance considerations, and data completeness.
Query-based
This method relies on a watermark column which is typically a timestamp or row identifier. As such, this depends on whether the SAP data object has a watermark column to expose for CDC. If a watermark column doesn’t exist, then development efforts would be required to create one. Of note, some SAP data objects store date watermark columns as string data types which need to be corrected to datetime data types for query-based CDC to work. Despite potentially needing additional development to expose watermark columns for SAP data objects, the benefits of real-time integration with query-based CDC could make this endeavor worth it.
Key takeaway: Easiest to implement but requires a watermark column across large SAP data objects which may not be readily available
ICYMI: Boomi for SAP Data Connector was released in Oct 2025 and supports timestamps, epochs, and running numbers as watermark columns.
Trigger-based
Trigger-based CDC is a step up from query-based CDC being more complete in data capture; the latter’s application level queries can’t detect source system deletions. Trigger-based CDC may operate at the application layer or database layer depending on how the trigger events are set up to be captured by the CDC service. For example, SAP Business Object Repository (BOR) change events are recognized by Boomi for SAP and processed via the Boomi Event Streams message system to enable trigger-based CDC. The recommended application layer approach leverages existing SAP objects and solves the SAP license compliance issue for Runtime customers. Whereas, the less ideal database layer approach will require database access to create new change event tables to capture trigger events.
Key takeaway: Most cost-effective CDC method available today for complete and real-time SAP data extraction for customers with a Runtime license
Announcement: Boomi for SAP Data Connector has a trigger-based CDC feature supporting SAP Business Objects available in Jan 2025
Log-based
While the log-based CDC method is most ideal for capturing your SAP data changes, this method isn’t always feasible in practice due to SAP licensing terms. Under the widely used Runtime license or Runtime Edition for Applications and BW (REAB) license, customers are restricted from SAP database layer access which is required to access database logs for log-based CDC to work. Customers will need additional or upgraded Full Use licenses to do so in order to comply with SAP usage rights. As a result, log-based CDC may become extremely costly to implement with Full Use licenses being an operational blocker. This CDC method is advisable if your organization has SAP ECC running on an Oracle or Microsoft SQL Server database and the database license was purchased directly from the vendor.
Key takeaway: Most ideal CDC method but not practical without existing Full Usage license or a database license purchased directly from the database vendor due to SAP license usage rights restricting database layer access
The Verdict
The case for using CDC for your SAP data is clear: either use it to fuel SAP analytics and agentic workflows or miss out on the SAP AI fast track. With agentic tools for SAP becoming more widely accessible, it’s imperative to ensure that your data foundations are ready to power your organization’s agentic transformation journey. This could mean modernizing your SAP data strategy to include CDC data pipelines that seamlessly fuel your cloud data lakehouse and even your SAP AI agents.
Boomi is trusted by enterprises worldwide with thousands of existing SAP connectors in production relied on by businesses to process their critical workloads. With Boomi for SAP’s new CDC connector feature, Boomi continues to use its proven, trusted technology to help customers get the most out of their SAP investment. Beyond connecting SAP to non-SAP systems, the Boomi for SAP Data Connector helps unlock the SAP data goldmine to connect SAP to everything AI and analytics.
Interested in learning how Boomi for SAP’s CDC feature could help you move your SAP data? Take a product tour or speak with a data expert today!