Built for Data Teams
Reliable pipelines with operational visibility, resumable syncs, and structured logging. Spend time on analysis, not pipeline maintenance.
The challenge
Pipeline failures require manual investigation
When a sync fails at 3 AM, someone has to log in, read unstructured logs, figure out what broke, and restart the job manually.
Building connectors takes weeks
Every new data source means writing a custom extraction script, handling pagination, retries, rate limits, and incremental logic from scratch.
Maintenance overhead grows with every pipeline
Each pipeline adds monitoring, alerting, and on-call burden. At ten pipelines, the team spends more time on infrastructure than analysis.
How StreamFlows solves it
Automatic retry and resume
Transient failures retry automatically with backoff. Persistent failures checkpoint so the next run picks up where the last one stopped.
Structured logging with correlation IDs
Every run, stream, and batch carries a correlation ID. Query logs by pipeline, status, or time range without parsing unstructured text.
Operational visibility
Row counts, durations, error messages, and stream-level detail for every run. See exactly what happened without guessing.
Pre-built connectors
Databases, SaaS APIs, and warehouses are supported out of the box. Schema discovery, pagination, and rate limiting are handled for you.
Relevant connectors
StreamFlows connects to the tools your team already uses.
How your data flows
From your sources through StreamFlows into your destination warehouse.
Ready to consolidate your data?
Set up your first pipeline in minutes. Connect a source, pick your streams, and start syncing to your warehouse.