Debezium

About Debezium

An open-source CDC platform that monitors databases and streams every committed row-level change as a structured event. Debezium reads directly from database replication logs — capturing inserts, updates, and deletes in real time with no polling and no impact on query performance.

Key Features

• 1Supports PostgreSQL, MySQL, MariaDB, Oracle, SQL Server, and MongoDB via native replication log protocols
• 2Captures every committed insert, update, and delete as a structured before/after event with full row images
• 3Runs as Kafka Connect connectors, distributing change streams across Kafka topics with durable, ordered delivery
• 4Debezium Server mode provides a standalone deployment that sinks directly to Kinesis, Pub/Sub, Redis, RabbitMQ, and more — no Kafka required
• 5Guarantees event ordering per table and survives consumer restarts by resuming from the last committed offset

How Python Data Engineers Use Debezium

Python data engineers typically run Debezium as the CDC producer and write Python consumers of the change streams it generates. After deploying Debezium connectors via Docker Compose or Kubernetes, Python services consume CDC events from Kafka topics using confluent-kafka or kafka-python — receiving full before/after row images for every database change, which are then written as Parquet to S3 or applied as upserts to a data warehouse. For teams without Kafka, Debezium Server sinks directly to AWS Kinesis or Redis Streams, both of which have first-class Python client libraries (boto3, redis-py), keeping the Python integration straightforward.