In today's data-driven world, real-time monitoring of database changes is critical for applications like fraud detection and live analytics dashboards. This project demonstrates a robust real-time data pipeline using PostgreSQL, Debezium, and Kafka, orchestrated with Docker, to capture and stream database changes efficiently. The project includes:
- SQL scripts for creating triggers to track user actions and specific column changes.
- Docker Compose setup for Postgres, Kafka, Zookeeper, and Debezium.
- Python script for generating test data.
Features
- Real-time change data capture (CDC) with Debezium.
- Seamless integration with Kafka for streaming data.
- Advanced tracking of database modifications, including user and timestamp.
- Optimized for specific column changes to reduce data overhead.
Technology Used
- Postgres
- Debezium
- Kafka
- Docker
- Python
Learn More
Link: Read the full article on Medium
Code: https://github.com/shj37/Monitoring-Database-Changes-with-Postgres-Debezium-and-Kafka
