DatriseAI-first ETL

Snowflake to Metabase Integration

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

How Datrise loads Snowflake into Metabase

Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses into Metabase as clean SQL tables Metabase auto-discovers. Flexible or custom fields land in flattened columns for the question builder, and timestamps such as created, updated, and status changes are typed as temporal columns for trends.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for large questions. Metabase auto-scans schemas, so Datrise uses readable table and column names so the no-code UI stays self-explanatory.

Ideal for self-serve questions and dashboards for whole teams.

Endpoints

Snowflake: Cloud data platform with separated storage and compute.

Metabase: Open-source analytics with questions, dashboards, and embedded insights.

How Snowflake entities map to Metabase

Snowflake entityMetabase objectNotes
databasessnowflake_databasesid PK · custom fields → flattened columns for the question builder
schemassnowflake_schemasid PK · linked to snowflake_databases
tablessnowflake_tablesid PK · linked to snowflake_databases
viewssnowflake_viewsid PK · linked to snowflake_databases

FAQ

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

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

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

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

Related pipelines

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