The CDC Playbook: Zero-Delay Data Syncing
How do you keep your search engine (Elasticsearch) updated when a user changes their profile in your primary database (PostgreSQL)? Dual-writing in your application code is a recipe for data inconsistency. The solution is Change Data Capture (CDC).
1. The WAL Tailing Strategy
Debezium doesn't query your database. It tails the Write-Ahead Log (WAL).
- Benefit: Zero overhead on the database CPU. It captures every , , and as a raw event stream.
2. Architecture
- Source: PostgreSQL (Primary).
- Connector: Debezium running in Kafka Connect.
- Transport: Apache Kafka topic (e.g., ).
- Sink: Elasticsearch Sink Connector.
3. Handling Schema Changes
CDC handles schema evolution. If you add a column in Postgres, Debezium detects the change and updates the Kafka message structure, which the ES Sink can then use to update the index mapping.
Summary
CDC is the bridge between a relational source of truth and a specialized read model. It eliminates the "Dual Write" problem and provides a rock-solid foundation for Event-Driven architectures.
