DatriseAI-first ETL

LookML to Apache Superset Integration

AI-first ETL from LookML into Apache Superset. Governed entities, incremental sync, typed landing tables.

How Datrise loads LookML into Apache Superset

Datrise syncs LookML's models, explores, views, dimensions, measures, and joins into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

LookML: Semantic model definitions behind Looker content.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How LookML entities map to Apache Superset

LookML entityApache Superset objectNotes
modelslookml_modelsid PK · custom fields → flattened columns for the explore UI
exploreslookml_exploresid PK · linked to lookml_models
viewslookml_viewsid PK · linked to lookml_models
dimensionslookml_dimensionsid PK · linked to lookml_models

FAQ

How does Datrise handle LookML's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the LookML to Apache Superset sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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