Top Design & Implementation Challenges with Change Data Capture

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Why Change Data Capture Matters Now More Than Ever

The push towards real time data and streaming-first architectures has never been more pervasive than in our current big data and analytics landscape. The volume and velocity of data is ever increasing, causing strain on legacy architectures as they attempt to process it effectively. The complications of ingesting data from operational sources in near real time, transformed and optimized does not come without complexity.


Change Data Capture
is a low overhead and low latency method of extracting data, compared to traditional batch processes, limiting intrusion into the source and continuously ingesting and replicating data by tracking changes to the data. When designed and implemented effectively, CDC is the most efficient method to meet today’s scalability, efficiency, real-time and low overhead requirements.


It is imperative that your business has the right architecture in place to handle high throughput of data, a simplicity of replicating subsets of data and ever changing schema, as well as the capacity to capture the data and the changes exactly once, then replicate or ETL the CDC data to your data warehouse or data lakes, for analytics purposes.


Chapter One Title

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Chapter Two Title

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Chapter Three Title

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Chapter Four Title

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Chapter Five Title

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Chapter Six Title

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Chapter Seven Title

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Chapter Eight Title

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Chapter Nine Title

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Optimizing Streaming Architectures with Speed, Scalability, Simplicity and Modern CDC

Remember, CDC should be thought of as means to an end - a supplement to your Data Architecture and acting in service to your downstream data rather than a standalone effort.


Step One:
Identify your primary streaming use case.

Step Two:
See if you will have overlap in other use cases that could be accommodated by one tool versus many.

Step Three
: Aim for data architecture simplification to optimize operations, management, monitoring and system sustainability.



Regardless of the use case, some final considerations:

  • Simplify the streams of data - Complex data streams can lead to endless patch and fix corrections. Are there places where you could make your data architecture more efficient and easier to monitor? More performant? Safeguard your data and your time with simplicity and visibility.
  • Combine operations with one platform versus many - Seek to reduce the cost and complexity of multiple licenses and subscriptions in exchange for one platform that can perform all necessary functions with a single licensing fee. That said, don’t migrate everything on day one, start with green field use cases and migrate other use cases slowly that can benefit from the new platform.
  • Take advantage of a drag and drop UI versus complex custom coding in multiple tools - Diversify the talent that can engage with your data architecture by eliminating the need for heavy coding. Drag and drop interfaces streamline the process of onboarding, rollout, administration, maintenance and monitoring.
  • Explore platforms that make CDC ingestion fast and easy - Look for solutions with low overhead on source systems and the flexibility to change targets or sources with the click of a button. Replication groups to handle complex and large replications? Cloud agnostic? Even better.
  • Find a scalable multi-modal solution - Be ready to grow as your business expands and data volume and velocity increases. Need to maintain some batch processes as well as have streaming capability? Look for a solution that can accommodate both.



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Modern Change Data Capture is a vital component for a streaming-first data architecture. These guidelines and best practices will help achieve an optimized streaming pipeline architecture that will ingest data seamlessly and efficiently from any data source, including legacy data sources, enabling the analytics teams to provide the most enriched, up-to-date business insights to the organization decision makers. As streaming-first ingestion becomes the standard preferred data architecture to support business operations and visibility, you must make sure to have the right strategy in place to succeed.

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