How to implement CDC using Debezium, Kafka and Starburst Galaxy

The text provides a comprehensive guide on implementing Change Data Capture (CDC) using Debezium, Kafka, and Starburst Galaxy to synchronize data from PostgreSQL databases to a data lake in Apache Iceberg format. It details how Debezium captures and streams real-time changes using PostgreSQL's logical decoding, which are then streamed to Kafka topics, allowing for efficient data synchronization across systems. The guide includes prerequisites such as configuring a PostgreSQL database on Amazon RDS for logical replication, setting up a Kafka cluster with Docker, and connecting to AWS S3 for data storage. It further explains how to configure PostgreSQL and S3 connectors and provides a detailed example of using a SQL MERGE statement to update records in a data lake based on changes captured from source tables. This approach facilitates a decoupled architecture for handling data modifications and enables seamless data updates, deletions, and insertions across various systems.

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