Permit-office staff update a transactional database all day, and analysts need those changes as near-real-time events on Kafka. Which ingestion pattern fits?
Select an answer to reveal the explanation.
Short Explanation
When clerks edit the permit DB, those row changes can ride out as events—CDC is the tap on the pipe. Kafka then feeds analytics without waiting for a yearly dump or retyping. Live changes, streamed once.
Full Explanation
Change-data-capture style ingestion converts inserts, updates, and deletes from operational databases into event streams suitable for Kafka consumers. That pattern supports near-real-time civic analytics without annual full dumps, dual manual entry, or freezing OLTP writes. CDC decouples the transactional system of record from downstream Big Data processors while preserving a chronological change feed. It is a core modern ingestion awareness topic alongside messaging buses.