What are common data pipeline issues inside Change Data Capture (CDC)?

CDC pipelines often face issues such as data consistency gaps, where a transaction is partially captured, leading to duplicate or missing rows. Schema evolution can break downstream consumers if new columns are added without proper handling. Ordering guarantees are hard to maintain, especially with distributed sources, causing out‑of‑order events. Latency can increase if the capture process lags behind the source. Failure handling is critical; a crash may leave the pipeline in an inconsistent state. Integration with downstream systems may require transformation or enrichment, which can introduce bottlenecks. Monitoring metrics like lag, error rates, and throughput, along with automated recovery and replay mechanisms, are essential to mitigate these problems.