cdc-pipeline

Change data capture detects and captures data changes in source databases, propagating them as events to target systems for real-time data consistency. This event-driven synchronization ensures downstream systems receive updates in near real-time.

You need event-driven data synchronization when maintaining real-time data consistency across distributed systems is required. It is ideal for scenarios like synchronizing customer data updates from a primary database to a data warehouse or search index as they happen.

To implement change data capture and event-driven sync, you define the data sources, event streams, and target consumers. The process requires setting up robust error handling and validation to ensure data integration across systems.

Yes, this change data capture approach syncs data from a primary database to a search index by propagating changes as events. It ensures the search index always has the latest information by capturing source system updates in near real-time.

The best way to handle errors during event-driven data replication is by defining robust error handling and validation within your data sources and target consumers. This ensures reliable data synchronization across distributed systems.