Flink CDC — Real-Time Change Data Capture for Apache Flink

Introduction

Flink CDC brings change-data-capture into the Apache Flink ecosystem. It reads database transaction logs (binlog, WAL, oplog) and converts them into Flink streams, enabling real-time ETL, data lake ingestion, and cross-database synchronization without custom glue code.

What Flink CDC Does

• Reads binlog/WAL/oplog from MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, and more
• Delivers insert, update, and delete events as structured Flink DataStreams
• Supports full snapshot followed by continuous incremental capture in a single job
• Provides a YAML-based pipeline definition for codeless database-to-database sync
• Handles schema evolution by propagating DDL changes downstream automatically

Architecture Overview

Flink CDC connectors embed Debezium engines within Flink source operators. On startup a snapshot reader performs a parallel chunked scan of existing data, then hands off to a binlog reader for ongoing changes. Events are checkpointed using Flink exactly-once semantics so no data is lost or duplicated, even across restarts.

Self-Hosting & Configuration

• Deploy Apache Flink 1.18+ and add the appropriate CDC connector JARs to the lib directory
• Configure source database credentials and binlog/WAL access permissions
• Define a pipeline in YAML or write a Flink job in Java specifying source tables and sink targets
• Tune parallelism and checkpoint intervals for throughput and latency requirements
• Monitor via the Flink Web UI or integrate with Prometheus metrics

Key Features

• Exactly-once processing semantics for reliable data delivery
• Parallel snapshot reading using table chunk splitting for fast initial loads
• Schema evolution support propagates ALTER TABLE changes to downstream sinks
• Codeless YAML pipeline mode for common sync scenarios
• Compatible with the full Apache Flink ecosystem including SQL, Table API, and DataStream API

Comparison with Similar Tools

• Debezium — Standalone CDC platform using Kafka Connect; Flink CDC embeds Debezium inside Flink for tighter integration
• Airbyte — General ELT platform with CDC connectors, but batch-oriented rather than continuous streaming
• AWS DMS — Managed CDC service locked to AWS, not open source
• Canal — Alibaba MySQL binlog reader focused on MySQL-only use cases
• Maxwell — Lightweight MySQL-only binlog reader that writes to Kafka; no built-in transformation

FAQ

Q: Do I need Kafka to use Flink CDC? A: No. Flink CDC reads database logs directly without requiring an intermediate message queue.

Q: Which databases are supported? A: MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, Db2, OceanBase, TiDB, and Vitess, with the list growing.

Q: Can Flink CDC handle schema changes automatically? A: Yes. The pipeline mode can propagate DDL changes like column additions to supported sinks.

Q: What is the difference between Flink CDC and Debezium? A: Flink CDC uses Debezium internally but runs inside the Flink runtime, giving you access to Flink SQL, exactly-once checkpointing, and the full Flink ecosystem.

Sources

• https://github.com/apache/flink-cdc
• https://nightlies.apache.org/flink/flink-cdc-docs-stable/