Flow Engine vs Data Engine
The two engines share the same underlying node-graph model and editor, but they serve different purposes.| Flow Engine | Data Engine | |
|---|---|---|
| Purpose | Orchestration: run a process with side effects | Transformation: derive a value from other values |
| Side effects | Yes - steps call source/target systems, write logs, persist state | No - pure computation over values |
| Values that flow | Token assigns (string-keyed map of named values) | Dated properties |
| Top-level driver | A saved Flow with optional schedules | A property mapping, domain condition, or other value derivation |
| Runs | Each run is recorded as a FlowRun with logs and status | No run records; evaluation happens on demand inside another operation |
Where to start
Before building a flow, read the concept pages in order:- Flows and runs covers what a flow is, how it is triggered, and what a run records.
- Steps and assigns introduces the token threaded through a run and the assigns map that nodes use to share values.
- Execution and error handling covers graph traversal, branching, looping, and the policies that decide what happens when a step fails.
- Scheduling and observability covers cron schedules, per-node log floors, and the run history.