Column lineage at AST grain
BoltPipeline emits column-level edges parsed from the SQL itself. Dagster's lineage is asset-level — it knows asset A depends on asset B but not which columns of A came from which columns of B.
BoltPipeline is a SQL-pipeline compilation + certification platform; Dagster is an asset-centric orchestrator. Shared asset mental model, different layers.
BoltPipeline vs Dagster on the capabilities that drive the buying decision.
| Capability | BoltPipeline | Dagster |
|---|---|---|
| Pre-deploy certification (BLOCKS) | Yes | — |
| AST-derived column lineage | Yes | Partial |
| Asset-centric model | Yes | Yes |
| Python ops + sensors + schedules | — | Yes |
| Continuous drift detection | Yes | Partial |
| ML asset graph | — | Yes |
| Operator triage from drift | Yes | Partial |
BoltPipeline emits column-level edges parsed from the SQL itself. Dagster's lineage is asset-level — it knows asset A depends on asset B but not which columns of A came from which columns of B.
BoltPipeline shows the blast radius of a SQL change before commit — every downstream table, column, and dashboard affected. Dagster runs the asset, then you find out what broke.
BoltPipeline drift detection runs continuously and routes findings to a triage queue with owners. Dagster sensors can detect drift but the triage workflow is on you.
No. Dagster's asset materialization, Python ops, sensors, schedules, and ML asset graph are its strengths — keep them. BoltPipeline certifies the SQL that produces your assets and gates the deploy.
Dagster lineage is asset-level — it tracks which asset depends on which. BoltPipeline lineage is column-level and AST-derived, with the derivation expression on each edge. Different grain for different jobs.
Yes — they share the asset-centric mental model. Use BoltPipeline to author and certify the SQL; use Dagster to materialize the resulting assets and run sensors/schedules.
Try BoltPipeline against your live database — your data never leaves your environment.