Google BigQuery to Domo Integration

How Datrise loads Google BigQuery into Domo

Datrise syncs Google BigQuery's datasets, tables, views, query jobs, table schemas, and partitions into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

Google BigQuery: Serverless analytics warehouse on Google Cloud.

Domo: Cloud BI platform combining data integration and executive dashboards.

How Google BigQuery entities map to Domo

Google BigQuery entity	Domo object	Notes
datasets	`bigquery_datasets`	id PK · custom fields → flattened columns for Magic ETL
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 Domo?

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

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

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

Early access

Connect Google BigQuery to Domo the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.