Change data capture detects inserts, updates and deletes in a database and streams those changes to other systems. Targets stay in sync without repeated full reloads.
Data migration is moving data from one system, format or location to another while keeping it complete and correct. Typical cases are legacy database replacements and moves to the cloud.
ETL (extract, transform, load) cleans and reshapes data before loading it into a target system. ELT (extract, load, transform) loads raw data first and does the transformation inside the target, usually a warehouse.
Stream processing is computing on data continuously as each event arrives, so results update within seconds. It is the engine behind real-time data streaming, replacing waits for scheduled batch runs.
Apache Kafka is an open-source distributed event streaming platform. It stores streams of records in durable, ordered logs that many applications can publish to and read from independently.
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