Google BigQuery to Holistics Integration

How Datrise loads Google BigQuery into Holistics

Datrise syncs Google BigQuery's datasets, tables, views, query jobs, table schemas, and partitions into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

Google BigQuery: Serverless analytics warehouse on Google Cloud.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Google BigQuery entities map to Holistics

Google BigQuery entity	Holistics object	Notes
datasets	`bigquery_datasets`	id PK · custom fields → flattened columns for the modeling layer
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 Holistics?

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

How does the Google BigQuery to Holistics sync stay up to date?

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

Related pipelines

Early access

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