Keeping track of data changes across systems is crucial for maintaining data consistency and integrity in modern software applications. One common approach to achieving this is through the use of change data capture (CDC) mechanisms.
Here are some key methods for tracking data changes across systems:
- Change Data Capture (CDC): CDC involves capturing changes made to data in real-time and propagating them to other systems. This ensures that all systems stay up-to-date with the latest data changes.
- Log-based Replication: Log-based replication involves replicating data changes by reading transaction logs or database redo logs. This method provides an efficient way to track and propagate data changes across systems.
- Event Streaming: Event streaming platforms like Apache Kafka can be used to publish and subscribe to data change events. By leveraging event-driven architecture, organizations can track data changes and react to them in real-time.
By implementing these data synchronization mechanisms, organizations can effectively keep track of data changes across systems and ensure data consistency throughout their software ecosystem.
