Change Data Capture
The Change Data Capture (CDC) system allows you to capture changes made to data records in MapR-DB tables (JSON or binary) and propagate them to a MapR-ES topic.
These data changes are the result of inserts, updates, and deletions and are called change data records. Once the change data records are propagated to a topic, a MapR-ES/Kafka consumer application is used to read and process them.
Why Use Change Data Capture?
- To track changes occuring in a MapR-DB table and perform real-time processing on the data.
- To keep caches for search indexes (such as Elastic Search, Solr), materialized views, synchronization between data warehouses or data marts with data stored in MapR-DB in real time.
- To manage separate MapR-DB instances for transactional and reporting purposes and to keep them in sync in real time for real time analytics.
- To provide arbitrary external systems the ability to globally consume MapR-DB table changes.
How Do I Get Started?
The following topics provide information you need to understand the CDC feature, to setup and use CDC, the maprcli commands used to perform tasks, and to consume the data via your application.