Capture database changes in real time with connectors, schema control, and streaming transformations
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Capture and stream database changes reliably to lakes, warehouses, and caches
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.
Design Flink jobs with stateful operators, checkpoints, exactly-once sinks, and low-latency SLAs
Common questions about ai streaming cdc architecture generator
Use a schema registry, enforce compatibility, and handle breaking changes with versioned topics.
Partition by keys, use ordering guarantees, and deduplicate with sequence numbers or LSNs.
Use stream processors for transformations, filtering, masking, and enrichment before writing to sinks.
Enable exactly-once or at-least-once semantics, use idempotent writes, and monitor lag and DLQs.
Restrict DB privileges, mask sensitive fields, and encrypt in transit and at rest.
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