BigQuery ML locations

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

For information on 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 supports the following locations.

Regional locations

Region description Region name
Las Vegas us-west4
Los Angeles us-west2
Montréal northamerica-northeast1
Northern Virginia us-east4
Salt Lake City us-west3
São Paulo southamerica-east1
South Carolina us-east1
Finland europe-north1
Frankfurt europe-west3
London europe-west2
Zürich europe-west6
Asia Pacific
Hong Kong asia-east2
Mumbai asia-south1
Osaka asia-northeast2
Seoul asia-northeast3
Singapore asia-southeast1
Sydney australia-southeast1
Taiwan asia-east1
Tokyo asia-northeast1

Multi-regional locations

Multi-region description Multi-region name
Data centers within member states of the European Union1 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.

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