How to capture changed records in a database and propagate them to one or several other databases
Use change data capture to synchronize relational and non-relational data in real time
Change data capture is an advanced technology for data replication and database synchronization. It reduces the time and resource costs of data propagation and facilitates real-time data integration across the enterprise. Change data capture technology focuses on detecting transactions that modify records in a database in order to reapply those changes on a target database. It replicates heterogeneous data in real-time to support data migration, database synchronization, event detection, Big Data acquisition, etc.
Keeps multiple databases synchronized in an active/active or active/stand-by mode
Enhances standard ETL processes by collecting only the data that has changed
Eliminates the need for costly bulk data unloads
Replicates heterogeneous data between heterogeneous databases (DB2, IMS, Oracle, Postgre, SQL Server, Hadoop, Spark, PureData Analytics, Cassandra, etc.)
Detects key business events in real-time
Makes your business data available in real-time for Big Data treatment
Near real-time and asynchronous data replication
Multi-directional replication: Active / Active & Active / Stand-by
Supports data capture on relational and non-relational databases including DB2, Oracle, MySQL, SQLServer, Postgre, IMS and files
A non-intrusive solution that requires no changes to existing applications
Integrates conversion and filter features to transform data during replication
What you can do
- Capture database changes as they occur and/or on a periodic basis.