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Learn how to drive high availability, performance and scalability by using basic Kafka Streams to implement event-driven microservices.

Build Event-Driven Microservices with Kafka Streams | eBook

Building Event-Driven Microservices with Kafka Streams

understanding change data capture

Change Data Capture (CDC) is an alternative approach for batch ETL, enabling real-time data replication across databases. CDC can detect, capture, and move data from a source database as data changes, allowing a real-time data synchronization across downstream systems.

The first few sections of this document walk you through a fictitious online store use case, explain the ETL shortcomings, and introduce you to CDC concepts. Then we discuss how the CDC works, its benefits, and how to implement a CDC system at scale. We conclude the document by discussing potential use cases for CDC, along with popular technology choices to build a CDC system in production environments.


Change Data Capture (CDC) is a process that identifies when data is changed in a system, enabling these changes to propagate to other applications or systems.

Understanding Change Data Capture

In this eBook, we look at why Change Data Capture systems have become popular, discussing how CDC works and how to scale it. We explore potential use cases for CDC, along with popular technology choices to build a CDC system in production environments.