Google BigQuery integration

Google BigQuery data, in your warehouse.

A built-in ingestr connector: add credentials, pick tables, schedule it.

name: raw.events
type: ingestr
parameters:
  source_connection: google_bigquery
  source_table: 'events'
  destination: snowflake
  incremental_strategy: merge

$ bruin run assets/raw/google_bigquery.asset.yml

extract · Google BigQuery eventsincremental
load · snowflake raw.eventsmerged
checks · not_null, unique

Loaded and checked. Downstream models can run.

How it connects

Connected in three steps.

BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data.

01
Add a Google BigQuery connection with its credentials.
02
Pick the tables to load and how: replace, append or merge.
03
Bruin runs it on your schedule and checks every load.

Connection parameters

project-id: Your Google Cloud project ID
credentials_path: Path to service account JSON key file
location: Optional dataset location (e.g., US, EU)

Every way Google BigQuery works with Bruin

SourceBuilt-in ingestr sourceDocs →
DestinationBuilt-in ingestr destinationDocs →
Query engineRuns SQL and Python assetsDocs →

Tables

5 tables, ready to load.

events
users
transactions
products
sessions

Step-by-step

Pick a destination.

Google BigQuery → Snowflake

Read the guide

Google BigQuery → Databricks

Read the guide

Google BigQuery → Amazon Redshift

Read the guide

Google BigQuery → PostgreSQL

Read the guide

Google BigQuery → ClickHouse

Read the guide

Google BigQuery → DuckDB

Read the guide

Google BigQuery → MotherDuck

Read the guide

The platform

Part of the Bruin platform.

Data in, ready for everything downstream: the models, the checks, the lineage and the AI layer.

See the full platform

Sources

DatabasesWarehousesApps & APIsFiles & storageStreams & webhooksWeb scraping

Move

Data Ingestion

Model & govern

SQL & Python Data Quality Data Governance

Self-Healing Pipelines

Use

AI Data Analyst AI Dashboards Data Apps Scheduled Agents Reverse ETL

Bruin Cloud runs every step

Warehouses & lakes

More tools, same category.

All 47 Warehouses & lakes tools

Snowflake Built in Databricks Built in Amazon Redshift Built in ClickHouse Built in DuckDB Built in MotherDuck Built in Microsoft Fabric Built in Microsoft OneLake Built in

Frequently asked

Questions about Google BigQuery.

Does Bruin have a built-in Google BigQuery integration?

Yes. Built-in ingestr source. Built-in ingestr destination. Runs SQL and Python assets.

Which Google BigQuery tables can Bruin load?

events, users, transactions, products, sessions.

Where can Google BigQuery data go?

Snowflake, BigQuery, Databricks, Redshift, ClickHouse, Postgres, DuckDB, MotherDuck, Microsoft Fabric and more, plus files on S3 and GCS.

How fresh is the data?

As fresh as your schedule. Incremental loads append, merge or replace a time window, every few minutes if you like.

Do we need Bruin Cloud?

No. The Bruin CLI and ingestr run locally, in CI or in your own orchestrator. Bruin Cloud adds scheduling, lineage, alerts and the AI data analyst on top.