This is the second part of the blog series which provides a step-by-step walkthrough of data pipelines with Kafka and Kafka Connect. I will be using AWS for demonstration purposes, but the concepts apply to any equivalent options (e.g. running these locally in Docker).
This part will show Change Data Capture in action that lets you track row-level changes in database tables in response to create, update and delete operations. For example, in MySQL, these change data events are exposed via the MySQL binary log (binlog).