Data Capture

Enterprise Ecosystem: Change Data Capture (Organized Chaos)

The technological landscape of the modern enterprise is complex. The need to continuously build, scale, and maintain the entire ecosystem is an omnipresent force that we constantly trade off against the need to deliver on time—or better yet—ahead of schedule. Strategies that organizations use to appropriately balance this trade-off are numerous, multifaceted and vary widely. Think about defining SDLC processes, identifying technologies to be used, system architecture, resource allocation planning, tool adoption & licensing etc.

This post delves into the concept of Change Data Capture. Specifically, how it can be used at scale to build a unified event backbone that establishes data-level consistency and event-driven architectures across distributed systems.

Specific areas that we touch on:

– Change Data Capture (CDC) Use Cases

– Associated Advantages & Disadvantages

– Technology Options for Getting Started

CDC Use Cases:

Point to Point


Event Driven, Consistent, Database Exposed


Complete Separation of Concerns (Micro-services Oriented)


Strong use cases for DB level change data capture include the following:

CDC Advantages and Disadvantages

Technologies and Options