Capture and stream database changes reliably to lakes, warehouses, and caches
No sign-up required • Free to try
Capture database changes in real time with connectors, schema control, and streaming transformations
A data pipeline diagram shows where data comes from, the jobs that move and transform it, and where it lands. Describe yours and get an editable diagram with the right icons in seconds.
Diagram Kafka Connect clusters with connectors, SMTs, converters, and reliability patterns
Common questions about ai change data capture generator
Use log-based connectors for low impact. Avoid triggers when possible to reduce DB load.
Version schemas, enforce compatibility, and migrate downstream consumers with deprecation windows.
Partition by primary key and include metadata for ordering and deduplication. Use idempotent upserts.
Send bad events to DLQs with reason codes. Reprocess after fixes with replay tooling.
Encrypt, restrict topics, and mask sensitive columns before publishing. Audit access to change streams.
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