Google BigQuery to Metabase Integration

How Datrise loads Google BigQuery into Metabase

Datrise syncs Google BigQuery's datasets, tables, views, query jobs, table schemas, and partitions 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

Google BigQuery: Serverless analytics warehouse on Google Cloud.

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

How Google BigQuery entities map to Metabase

Google BigQuery entity	Metabase object	Notes
datasets	`bigquery_datasets`	id PK · custom fields → flattened columns for the question builder
tables	`bigquery_tables`	id PK · linked to bigquery_datasets
views	`bigquery_views`	id PK · linked to bigquery_datasets
query jobs	`bigquery_query_jobs`	id PK · linked to bigquery_datasets

FAQ

How does Datrise handle Google BigQuery'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 Google BigQuery to Metabase sync stay up to date?

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

Related pipelines

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