DatriseAI-first ETL

Metabase to Redash Integration

AI-first ETL from Metabase into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Metabase into Redash

Datrise syncs Metabase's questions, dashboards, collections, cards, users, and query executions into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Metabase: Self-service BI over existing databases.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Metabase entities map to Redash

Metabase entityRedash objectNotes
questionsmetabase_questionsid PK · custom fields → flattened columns for query results
dashboardsmetabase_dashboardsid PK · linked to metabase_questions
collectionsmetabase_collectionsid PK · linked to metabase_questions
cardsmetabase_cardsid PK · linked to metabase_questions

FAQ

How does Datrise handle Metabase's custom fields in Redash?

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

How does the Metabase to Redash sync stay up to date?

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

Related pipelines

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