Why Database Change Data Capture Needs Exactly-Once Semantics

Episode 123 of Database Tech with Fexingo. Lucas and Luna dissect a production nightmare: CDC pipelines delivering duplicate events to a downstream analytics warehouse. They explain why change data capture without exactly-once semantics leads to phantom revenue numbers, and how tools like Debezium and Kafka handle offset commits, idempotent sinks, and out-of-order events. Using a concrete example of a $200 million reconciliation error at a real fintech firm, they walk through the four mechanisms that make CDC reliable: source offset tracking, transactional log position, sink idempotency, and deduplication windows. Perfect for data engineers who think CDC is 'just streaming' and want the low-level guarantees that prevent silent corruption. #ChangeDataCapture #ExactlyOnceSemantics #CDC #Debezium #ApacheKafka #DataEngineering #StreamingData #DataPipelines #DatabaseReplication #PostgreSQL #MySQL #KafkaConnect #EventDriven #DataIntegrity #DatabaseTechWithFexingo #FexingoBusiness #BusinessPodcast #Technology Keep every episode free: buymeacoffee.com/fexingo