What is change data capture?
Change data capture retrieves changed data from a DBMS or other data store. See the Change data capture Wikipedia article for an overview.
Change data capture using logs
Relational database management systems use write-ahead logs, also called redo or transaction logs, that represent DML and DDL changes. Traditionally, RDBMS systems use these logs to guarantee ACID properties and support rollback and roll-forward recovery operations. As DBMS technology has evolved, these logs have been augmented to record additional types of changes. Today they may track virtually every redoable and undoable action in the system, including transaction start and commit boundaries, table and index changes, data definition changes, rollback operations, indicators of non-logged changes, and more.
DBMS vendors and third parties have found additional uses for these logs. Striim, for example, can extract change data from logs in real time in order to make information available before the DBMS has finished processing it, at the same time minimizing the performance load on the RBMS by eliminating additional queries. There are many potential uses for this information, such raising alerts about error conditions sooner and double-checking DBMS operations in order to identify lost data.
All of the readers discussed in this Change Data Capture Guide capture change data by reading logs.
Change data capture using JDBC
You can use Striim's Incremental Batch Reader to capture change data using JDBC based on timestamps or incrementing values.