Map structured streaming jobs with checkpoints, watermarks, and exactly-once sinks
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.
Common questions about ai spark streaming architecture generator
Use idempotent sinks (Delta/Iceberg) and checkpoints for offsets. Avoid side effects without deduplication.
Set watermarks and allowed lateness. Recompute windows and manage state TTLs.
Adjust micro-batch intervals, use autoscaling, and optimize partitions and state store.
Track batch duration, input rates, state size, and lag. Alert on checkpoint failures.
Use schema inference carefully; prefer explicit schemas and handle evolution via schema registry.
Try it free on the scratch canvas, no account needed. Pro starts with a 7-day free trial.