Debezium is an open source distributed platform for change data capture. Start it up, point it at your databases, and your apps can start responding to all of the inserts, updates, and deletes that other apps commit to your databases. Debezium is durable and fast, so your apps can respond quickly and never miss an event, even when things go wrong.

Debezium's platform is  dedicated to providing insights and resources for developers and data engineers interested in change data capture (CDC) and event streaming architectures. Through articles, tutorials, and documentation, Debezium offers insights into capturing database changes, streaming data to Apache Kafka, and building real-time data pipelines. Developers can learn about CDC connectors, data integration patterns, and event-driven architectures to enable real-time analytics and stream processing.

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Change Data Capture (CDC) is essential for replicating operational data for analytics, and Debezium is a leading tool in this space, connecting to various databases and exporting CDC events in formats like JSON and Avro. This post demonstrates how to implement a Python-powered CDC pipeline using Debezium and pydbzengine, capturing change data from PostgreSQL and loading it into DuckDB with the Data Load Tool (DLT). The guide includes a code walkthrough, from setting up the environment and configuring Debezium to executing the pipeline and querying the results in DuckDB.

Real-time Data Replication with Debezium and Python