Locations

BigQuery   |  BigQuery ML   |  BigQuery BI Engine   |  BigQuery Data Transfer Service

This page explains the concept of data location and the different locations where you can create BigQuery datasets and BigQuery ML models.

For information about regional pricing for BigQuery ML, see the Pricing page.

Key concepts

Locations or region types

There are two types of locations:

• A region is a specific geographic place, such as London.

• A multi-region is a large geographic area, such as the United States, that contains two or more geographic places.

Dataset location

You specify a location for storing your BigQuery data when you create a dataset to store your BigQuery ML models and training data. After you create the dataset, the location cannot be changed, but you can copy the dataset to a different location, or manually move (recreate) the dataset in a different location.

BigQuery ML processes and stages data in the same location as the target dataset.

BigQuery ML stores your data in the selected location in accordance with the Service Specific Terms.

Supported regions

Like BigQuery, BigQuery ML is a regional and a multi-regional resource.

BigQuery ML model prediction and other ML functions are supported in the same regions as BigQuery.

Not all kinds of model training are supported in all regions.

Training models

• Training for built-in models (linear regression, logistic regression, kmeans, matrix factorization, and time series) is supported in all the same regions as model prediction and other ML functions.

• Imported models are supported in all the same regions as model prediction and other ML functions.

• Training for DNN and Boosted Trees using XGBoost models is available in the multi-regions US and EU, and most single regions. See the Regional locations table for more information.

• Training for AutoML tables is supported in the multi-regions US and EU.

Note: The following models are in a pre-release state and might change or have limited support: matrix factorization, time series, DNN, Boosted Trees, and AutoML tables. For more information, see the product launch stages.

Model prediction and other ML functions

BigQuery ML supports the following locations.

Regional locations

	Region description	Region name	Imported models	Built-in model training	DNN/Boosted Tree model training	AutoML model training
Americas
	Las Vegas	us-west4	●	●
	Los Angeles	us-west2	●	●	●
	Montréal	northamerica-northeast1	●	●	●
	Northern Virginia	us-east4	●	●	●
	Oregon	us-west1	●	●	●
	Salt Lake City	us-west3	●	●	●
	São Paulo	southamerica-east1	●	●	●
	South Carolina	us-east1	●	●	●
Europe
	Belgium	europe-west1	●	●	●
	Finland	europe-north1	●	●	●
	Frankfurt	europe-west3	●	●	●
	London	europe-west2	●	●	●
	Netherlands	europe-west4	●	●	●
	Zürich	europe-west6	●	●	●
Asia Pacific
	Hong Kong	asia-east2	●	●	●
	Jakarta	asia-southeast2	●	●
	Mumbai	asia-south1	●	●	●
	Osaka	asia-northeast2	●	●	●
	Seoul	asia-northeast3	●	●	●
	Singapore	asia-southeast1	●	●	●
	Sydney	australia-southeast1	●	●	●
	Taiwan	asia-east1	●	●	●
	Tokyo	asia-northeast1	●	●	●

Multi-regional locations

Region description	Region name	Imported models	Built-in model training	DNN/Boosted Tree model training	AutoML model training
Data centers within member states of the European Union^1	EU	●	●	●	●
Data centers in the United States	US	●	●	●	●

¹ Data located in the EU multi-region is not stored in the europe-west2 (London) or europe-west6 (Zürich) data centers.

What's next

• Read an overview of BigQuery ML
• To get started using BigQuery ML, see Getting started with BigQuery ML using the Cloud Console.
• View all the Google Cloud services available in locations worldwide.
• Explore additional location-based concepts, such as zones, that apply to other Google Cloud services.