Change data capture (CDC) is a technique for detecting inserts, updates and deletes in a source database and delivering only those changes to downstream systems, usually by reading the database transaction log. It keeps analytics platforms current without repeatedly copying whole tables.
Log-based CDC tools such as Debezium publish changes as events, often through Apache Kafka, which pipelines then apply to lakehouse tables with MERGE operations.
Read more about Change data capture (CDC)
- CDC into the Lakehouse: Idempotent MERGE, SCD Type 2, Deletes and Out-of-Order DataEngineering change data capture on Delta Lake: deduplication, sequence guards, soft deletes, SCD2 in one MERGE, rebuilding history for late data, idempotent streams.
- Kafka Event Processing in Production: Ordering, Exactly-Once, Rebalancing and Failure HandlingPartitioning and ordering, durable producers, transactions and exactly-once limits, consumer rebalancing, retries and DLQs, schema evolution and Spark streaming on Kafka.
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