Change Data Capture (CDC)
Change Data Capture (CDC) enables real-time tracking and streaming of data modifications in your Tacnode database. This guide covers essential concepts and practical implementation for robust data synchronization across your systems.
Overview
Change Data Capture is a technique that identifies and captures changes made to data in a database, then delivers those changes in real-time to downstream systems. This enables:
- Real-time data synchronization between systems
- Event-driven architectures based on data changes
- Data warehousing with near-zero latency
- Audit trails and compliance monitoring
CDC Architecture in Tacnode
Component | Purpose | Key Features |
---|---|---|
Publications | Define what data to replicate | Table selection, operation filtering |
Replication Slots | Track consumer progress | At-least-once delivery, WAL retention |
Logical Decoding | Convert WAL to readable format | Real-time processing, multiple formats |
Decoding Plugins | Output format control | test_decoding , pgoutput |
Core Concepts
Publications define the scope of data replication by specifying which tables to monitor and which operations to capture (INSERT, UPDATE, DELETE, TRUNCATE).
Replication Slots are server-side mechanisms that track consumer progress, ensure WAL entries aren't deleted prematurely, and guarantee at-least-once delivery.
Logical Decoding transforms the internal WAL format into a client-readable stream in real-time.
Decoding Plugins: Tacnode supports test_decoding
(SQL-like text for testing) and pgoutput
(binary format for production).
Prerequisites and Setup
Configure your database for logical replication:
For comprehensive change tracking, set replica identity:
REPLICA IDENTITY FULL
increases WAL size but provides complete change information, essential for handling UPDATE and DELETE operations without primary keys.
Working with Publications
Publications define the data change subscription scope for your CDC setup.
Creating Publications
Managing Publications
Working with Replication Slots
Replication slots ensure reliable change delivery and prevent data loss.
Creating Replication Slots
Monitoring Replication Slots
Managing Replication Slots
Practical Examples
E-commerce Order Tracking Setup
Testing CDC with pg_logical Functions
Integration with Apache Flink
Apache Flink provides excellent CDC integration through the postgres-cdc connector.
For detailed Flink CDC configuration and examples, refer to the Apache Flink Integration documentation.
Troubleshooting Common Issues
Slot Lag Issues
- Check consumer application health and processing capacity
- Monitor lag with:
SELECT pg_size_pretty(pg_wal_lsn_diff(pg_current_wal_lsn(), confirmed_flush_lsn)) FROM pg_replication_slots WHERE slot_name = 'your_slot';
- Consider advancing slot position if safe:
SELECT pg_replication_slot_advance('slot_name', pg_current_wal_lsn());
Consumer Connection Problems
- Verify network connectivity and authentication
- Check active connections:
SELECT r.application_name, r.client_addr, s.slot_name FROM pg_stat_replication r RIGHT JOIN pg_replication_slots s ON r.pid = s.active_pid;
Missing Change Events
- Verify table is included in publication:
SELECT tablename FROM pg_publication_tables WHERE pubname = 'your_publication';
- Check operation types enabled:
SELECT pubinsert, pubupdate, pubdelete FROM pg_publication WHERE pubname = 'your_publication';
- Ensure replica identity is properly configured
Security Considerations
Access Control
Network Security
- Use SSL/TLS for replication connections
- Implement firewall rules for CDC consumers
- Consider VPN for cross-region replication
- Monitor connection attempts and failures
By following these guidelines and best practices, you'll build reliable CDC solutions that scale with your data and business needs.
For specific integration patterns, refer to: