BigQuery locations

This page explains the concept oflocation and the different regionswhere data can be stored and processed. Pricing for storage and analysis is alsodefined by location of data and reservations. For more information about pricingfor locations, seeBigQuery pricing. To learnhow to set the location for your dataset, seeCreate datasets. Forinformation about reservation locations, seeManaging reservations in differentregions.

For more information about how the BigQuery Data Transfer Service uses location, seeData location and transfers.

Locations and regions

BigQuery provides two types of data and compute locations:

• Aregion is a specific geographic place, such as London.

• Amulti-region is a large geographic area, such as the United States orEurope, that contains many unique and discrete regions. Multi-region locations canprovide larger quotas than single regions, but multi-regions don'tprovide regional redundancy. Data isstored in a single region and compute is only provided within that region. Forcross-region redundancy BigQuery offersmanaged disasterrecovery.

For either location type, BigQuery automatically stores copies ofyour data in two different zones within a single region in the selectedlocation. Multi-regions are considered separate from other regions, even whenlocated within the same zone. For more information about data availability anddurability, seeDisasterplanning.

Supported locations

BigQuery datasets can be stored in the following regions andmulti-regions. For more information about regions and zones, seeGeography and regions.

Regions

The following table lists the regions in the Americas where BigQuery is available.

Region description	Region name	Details
Columbus, Ohio	us-east5
Dallas	us-south1	Low CO2
Iowa	us-central1	Low CO2
Las Vegas	us-west4
Los Angeles	us-west2
Mexico	northamerica-south1
Montréal	northamerica-northeast1	Low CO2
Northern Virginia	us-east4
Oregon	us-west1	Low CO2
Salt Lake City	us-west3
São Paulo	southamerica-east1	Low CO2
Santiago	southamerica-west1	Low CO2
South Carolina	us-east1
Toronto	northamerica-northeast2	Low CO2

The following table lists the regions in Asia Pacific where BigQuery is available.

Region description	Region name	Details
Bangkok	asia-southeast3
Delhi	asia-south2
Hong Kong	asia-east2
Jakarta	asia-southeast2
Melbourne	australia-southeast2
Mumbai	asia-south1
Osaka	asia-northeast2
Seoul	asia-northeast3
Singapore	asia-southeast1
Sydney	australia-southeast1
Taiwan	asia-east1
Tokyo	asia-northeast1

The following table lists the regions in Europe where BigQuery is available.

Region description	Region name	Details
Belgium	europe-west1	Low CO2
Berlin	europe-west10
Finland	europe-north1	Low CO2
Frankfurt	europe-west3
London	europe-west2	Low CO2
Madrid	europe-southwest1	Low CO2
Milan	europe-west8
Netherlands	europe-west4	Low CO2
Paris	europe-west9	Low CO2
Stockholm	europe-north2	Low CO2
Turin	europe-west12
Warsaw	europe-central2
Zürich	europe-west6	Low CO2

The following table lists the regions in the Middle East where BigQuery is available.

Region description	Region name	Details
Dammam	me-central2
Doha	me-central1
Tel Aviv	me-west1

The following table lists the regions in Africa where BigQuery is available.

Region description	Region name	Details
Johannesburg	africa-south1

Multi-regions

The following table lists the multi-regions where BigQuery is available. When you select amulti-region, you let BigQuery select a single region within themulti-region where your data is stored and processed.

Multi-region description	Multi-region name
Data centers withinmember states of the European Union1	EU
Data centers in the United States2	US

Note: Selecting a multi-region location does not provide cross-region replication or regional redundancy, so there is no increase in dataset availability in the event of a regional outage. Data is stored in a single region within the geographic location.

¹ Data located in theEU multi-region is onlystored in one of the following locations:europe-west1 (Belgium) oreurope-west4 (Netherlands).The exact location in which the data is stored and processed is determined automatically by BigQuery.

² Data located in theUS multi-region is onlystored in one of the following locations:us-central1 (Iowa),us-west1 (Oregon), orus-central2 (Oklahoma). The exactlocation in which the data is stored and processed is determinedautomatically by BigQuery.

BigQuery Studio locations

BigQuery Studio lets you save, share, and manage versions of code assetssuch asnotebooks andsaved queries.

The following table lists the regions where BigQuery Studio is available:

	Region description	Region name	Details
Africa
	Johannesburg	africa-south1
Americas
	Columbus	us-east5
	Dallas	us-south1	Low CO2
	Iowa	us-central1	Low CO2
	Las Vegas	us-west4
	Los Angeles	us-west2
	Mexico	northamerica-south1
	Montréal	northamerica-northeast1	Low CO2
	North Virginia	us-east4
	Oklahoma	us-central2	Low CO2
	Oregon	us-west1	Low CO2
	Salt Lake City	us-west3
	Santiago	southamerica-west1	Low CO2
	São Paulo	southamerica-east1	Low CO2
	South Carolina	us-east1
	Toronto	northamerica-northeast2	Low CO2
Asia Pacific
	Bangkok	asia-southeast3
	Delhi	asia-south2
	Hong Kong	asia-east2
	Jakarta	asia-southeast2
	Melbourne	australia-southeast2
	Mumbai	asia-south1
	Osaka	asia-northeast2
	Seoul	asia-northeast3
	Singapore	asia-southeast1
	Sydney	australia-southeast1
	Taiwan	asia-east1
	Tokyo	asia-northeast1
Europe
	Belgium	europe-west1	Low CO2
	Berlin	europe-west10
	Finland	europe-north1	Low CO2
	Frankfurt	europe-west3
	London	europe-west2	Low CO2
	Madrid	europe-southwest1	Low CO2
	Milan	europe-west8
	Netherlands	europe-west4	Low CO2
	Paris	europe-west9	Low CO2
	Stockholm	europe-north2	Low CO2
	Turin	europe-west12
	Warsaw	europe-central2
	Zürich	europe-west6	Low CO2
Middle East
	Dammam	me-central2
	Doha	me-central1
	Tel Aviv	me-west1

BigQuery Omni locations

BigQuery Omni processesqueries in the same location as the dataset that contains the tables you'requerying. After you create the dataset, the location cannot be changed. Yourdata resides within your AWS or Azure account. BigQuery Omni regionssupport Enterprise edition reservations and on-demand compute (analysis)pricing. For more information about editions, seeIntroduction to BigQuery editions.

	Region description	Region name	Colocated BigQuery region
AWS
	AWS - US East (N. Virginia)	aws-us-east-1	us-east4
	AWS - US West (Oregon)	aws-us-west-2	us-west1
	AWS - Asia Pacific (Seoul)	aws-ap-northeast-2	asia-northeast3
	AWS - Asia Pacific (Sydney)	aws-ap-southeast-2	australia-southeast1
	AWS - Europe (Ireland)	aws-eu-west-1	europe-west1
	AWS - Europe (Frankfurt)	aws-eu-central-1	europe-west3
Azure
	Azure - East US 2	azure-eastus2	us-east4

BigQuery ML locations

The following sections describe supported locations for BigQuery MLmodels.

Locations for remote models

This section contains information about supported locations forremote models,and about where remote model processing occurs.

Regional locations

See the following documentation for supported locations for remote models over Google models andpartner models:

• For Gemini model and embedding model supported regions, seeGoogle model endpoint locations.
• For Claude, Llama, and Mistral AI model supported regions, seeGoogle Cloud partner model endpoint locations.

The following table shows which regions are supported for remote models over Cloud AI servicesand custom models deployed to Vertex AI. The column name indicates the type ofremote model.

	Region description	Region name	Vertex AI deployed models	Cloud Natural Language API	Cloud Translation API	Cloud Vision API	Document AI API	Speech-to-Text API
Americas
	Columbus, Ohio	us-east5
	Dallas	us-south1	●
	Iowa	us-central1	●					●
	Las Vegas	us-west4	●
	Los Angeles	us-west2	●
	Mexico	northamerica-south1
	Montréal	northamerica-northeast1	●
	Northern Virginia	us-east4	●
	Oregon	us-west1	●					●
	Salt Lake City	us-west3	●
	São Paulo	southamerica-east1	●
	Santiago	southamerica-west1
	South Carolina	us-east1	●					●
	Toronto	northamerica-northeast2	●
Europe
	Belgium	europe-west1	●					●
	Finland	europe-north1
	Frankfurt	europe-west3	●					●
	London	europe-west2	●					●
	Madrid	europe-southwest1
	Milan	europe-west8	●
	Netherlands	europe-west4	●					●
	Paris	europe-west9	●
	Stockholm	europe-north2
	Turin	europe-west12
	Warsaw	europe-central2	●
	Zürich	europe-west6	●
Asia Pacific
	Bangkok	asia-southeast3
	Delhi	asia-south2
	Hong Kong	asia-east2	●
	Jakarta	asia-southeast2	●
	Melbourne	australia-southeast2
	Mumbai	asia-south1	●					●
	Osaka	asia-northeast2
	Seoul	asia-northeast3	●
	Singapore	asia-southeast1	●					●
	Sydney	australia-southeast1	●					●
	Taiwan	asia-east1	●
	Tokyo	asia-northeast1	●					●
Middle East
	Dammam	me-central2
	Doha	me-central1
	Tel Aviv	me-west1	●

If the dataset in which you are creating the remote model is in a single region,the Vertex AI model endpoint must be in the same region. Ifyou specify the model endpoint URL, use the endpoint in the same regionas the dataset. For example, if the dataset is in theus-central1 region, thenspecify the endpointhttps://us-central1-aiplatform.googleapis.com/v1/projects/myproject/locations/us-central1/publishers/google/models/<target_model>.If you specify the model name, BigQuery ML automaticallychooses the endpoint in the correct region.

Multi-regional locations

Multi-regional support for remote models is as follows:

• Gemini models are supported in theUS andEUmulti-regions.
• Claude, Llama, and Mistral AI models in theUS multi-region can use the Vertex AI endpoint for any single region within theUS multi-region. Claude, Llama, and Mistral AI models in theEU multi-region can use the Vertex AI endpoint for any single region within theEU multi-region except foreu-west2 andeu-west6.
• Vertex AI deployed models aren't supported in either multi-region.
• Cloud AI servicesare supported in theUS andEU multi-regions.

If the dataset in which you are creating the remote model is in a multi-region,then the Vertex AI model endpoint must be in a region withinthat multi-region. For example, if the dataset is in theeu multi-region,then you could specify the URL for theeurope-west1 region endpoint,https://europe-west1-aiplatform.googleapis.com/v1/projects/myproject/locations/europe-west1/publishers/google/models/<target_model>.If you specify the model name instead of the endpoint URL,BigQuery ML defaults to using theeurope-west4 endpoint fordatasets in theeu multi-region, and to using theus-central1 endpoint fordatasets in theus multi-region.

Global endpoint

Forsupported Gemini models,you can specify theglobal endpoint.

The global endpoint covers the entire world and provideshigher availability and reliability than a single region. Usingthe global endpoint for your requests can improve overallavailability while reducing resource exhausted (429) errors, which occurwhen you exceed your quota for a regional endpoint.If you want to use Gemini 2.0+ in a region where it isn'tavailable, you can avoid migrating your data to a different region byusing the global endpoint instead. You can only use a model deployed tothe global endpoint with theAI.GENERATE_TEXT function.

Don't use the global endpoint if you have requirements for the dataprocessing location, because when you use the global endpoint, you can'tcontrol or know the region where your processing requests are handled.

Processing locations for Google models and partner models

For information about processing locations used by Google models hosted inVertex AI, seeML processing for Google Cloud models.This information covers models deployed to regions or multi-regions. Models that use the globalendpoint don't guarantee any particular processing location.

For information about processing locations used by partner models hosted inVertex AI, seeML processing for Google Cloud partner models.

Locations for non-remote models

This section contains information about supported locations formodels other than remotemodels, and about where model processing occurs.

Regional locations

The following table contains information about supported locations for all model types other thanremote models:

	Region description	Region name	Imported models	Built-in model training	DNN/Autoencoder/ Boosted Tree/ Wide-and-Deep models training	AutoML model training	Hyperparameter tuning	Vertex AI Model Registry integration
Americas
	Columbus, Ohio	us-east5	●	●
	Dallas	us-south1	●	●
	Iowa	us-central1	●	●	●	●	●	●
	Las Vegas	us-west4	●	●		●		●
	Los Angeles	us-west2	●	●	●			●
	Mexico	northamerica-south1	●	●
	Montréal	northamerica-northeast1	●	●	●	●	●	●
	Northern Virginia	us-east4	●	●	●	●	●	●
	Oregon	us-west1	●	●	●		●	●
	Salt Lake City	us-west3	●	●	●
	São Paulo	southamerica-east1	●	●	●	●
	Santiago	southamerica-west1	●	●
	South Carolina	us-east1	●	●	●		●	●
	Toronto	northamerica-northeast2	●	●		●
Europe
	Belgium	europe-west1	●	●	●	●	●	●
	Berlin	europe-west10	●	●
	Finland	europe-north1	●	●	●
	Frankfurt	europe-west3	●	●	●	●	●	●
	London	europe-west2	●	●	●	●	●	●
	Madrid	europe-southwest1	●	●
	Milan	europe-west8	●	●
	Netherlands	europe-west4	●	●	●	●	●	●
	Paris	europe-west9	●	●
	Stockholm	europe-north2	●	●
	Turin	europe-west12		●
	Warsaw	europe-central2	●	●
	Zürich	europe-west6	●	●	●	●	●	●
Asia Pacific
	Bangkok	asia-southeast3	●	●
	Delhi	asia-south2	●	●
	Hong Kong	asia-east2	●	●	●	●	●	●
	Jakarta	asia-southeast2	●	●				●
	Melbourne	australia-southeast2	●	●
	Mumbai	asia-south1	●	●	●	●		●
	Osaka	asia-northeast2	●	●	●
	Seoul	asia-northeast3	●	●	●	●	●	●
	Singapore	asia-southeast1	●	●	●	●	●	●
	Sydney	australia-southeast1	●	●	●	●	●	●
	Taiwan	asia-east1	●	●	●	●	●	●
	Tokyo	asia-northeast1	●	●	●	●	●	●
Middle East
	Dammam	me-central2		●
	Doha	me-central1		●
	Tel Aviv	me-west1	●	●
Africa
	Johannesburg	africa-south1	●	●

Multi-regional locations

All supported models other than remote models are supported in theUS andEU multi-regions.

Data located in theEU multi-region is not stored in theeurope-west2(London) oreurope-west6 (Zürich) data centers.

Vertex AI Model Registry integration is supported only for single region integrations. Ifyou send a multi-region BigQuery ML model to the Model Registry,then it is converted to a regional model in Vertex AI.A BigQuery ML multi-region US model is synced to Vertex AIus-central1 and a BigQuery ML multi-region EU model is synced toVertex AIeurope-west4. For single region models, there areno changes.

Processing locations

For models other than remote models, BigQuery ML processes and stages data in thesame location as the dataset that contains the data.

BigQuery ML stores your data in the selected location inaccordance with theService Specific Terms.

BigQuery SQL translator locations

When migrating data from your legacy data warehouse into BigQuery,you can use several SQL translators to translate your SQL queries into GoogleSQLor other supported SQL dialects. These include theinteractive SQL translator,theSQL translation API, and thebatch SQL translator.

The BigQuery SQL translators are available in the followingprocessing locations:

	Region description	Region name	Details
Asia Pacific
	Delhi	asia-south2
	Hong Kong	asia-east2
	Jakarta	asia-southeast2
	Melbourne	australia-southeast2
	Mumbai	asia-south1
	Osaka	asia-northeast2
	Seoul	asia-northeast3
	Singapore	asia-southeast1
	Sydney	australia-southeast1
	Taiwan	asia-east1
	Tokyo	asia-northeast1
Europe
	Belgium	europe-west1	Low CO2
	Berlin	europe-west10
	EU multi-region	eu
	Finland	europe-north1	Low CO2
	Frankfurt	europe-west3
	London	europe-west2	Low CO2
	Madrid	europe-southwest1	Low CO2
	Milan	europe-west8
	Netherlands	europe-west4	Low CO2
	Paris	europe-west9	Low CO2
	Stockholm	europe-north2	Low CO2
	Turin	europe-west12
	Warsaw	europe-central2
	Zürich	europe-west6	Low CO2
Americas
	Columbus, Ohio	us-east5
	Dallas	us-south1	Low CO2
	Iowa	us-central1	Low CO2
	Las Vegas	us-west4
	Los Angeles	us-west2
	Mexico	northamerica-south1
	Northern Virginia	us-east4
	Oregon	us-west1	Low CO2
	Québec	northamerica-northeast1	Low CO2
	São Paulo	southamerica-east1	Low CO2
	Salt Lake City	us-west3
	Santiago	southamerica-west1	Low CO2
	South Carolina	us-east1
	Toronto	northamerica-northeast2	Low CO2
	US multi-region	us
Africa
	Johannesburg	africa-south1
MiddleEast
	Dammam	me-central2
	Doha	me-central1
	Israel	me-west1

BigQuery continuous query locations

The following table lists the regions where continuous queries are supported:

	Region description	Region name	Details
Americas
	US multi-region	us
	Columbus	us-east5
	Dallas	us-south1	Low CO2
	Iowa	us-central1	Low CO2
	Las Vegas	us-west4
	Los Angeles	us-west2
	Mexico	northamerica-south1
	Montréal	northamerica-northeast1	Low CO2
	Northern Virginia	us-east4
	Oklahoma	us-central2	Low CO2
	Oregon	us-west1	Low CO2
	Salt Lake City	us-west3
	Santiago	southamerica-west1	Low CO2
	São Paulo	southamerica-east1	Low CO2
	South Carolina	us-east1
	Toronto	northamerica-northeast2	Low CO2
Asia Pacific
	Delhi	asia-south2
	Hong Kong	asia-east2
	Jakarta	asia-southeast2
	Melbourne	australia-southeast2
	Mumbai	asia-south1
	Osaka	asia-northeast2
	Seoul	asia-northeast3
	Singapore	asia-southeast1
	Sydney	australia-southeast1
	Taiwan	asia-east1
	Tokyo	asia-northeast1
Europe
	EU multi-region	eu
	Belgium	europe-west1	Low CO2
	Berlin	europe-west10
	Finland	europe-north1	Low CO2
	Frankfurt	europe-west3
	London	europe-west2	Low CO2
	Madrid	europe-southwest1	Low CO2
	Milan	europe-west8
	Netherlands	europe-west4	Low CO2
	Paris	europe-west9	Low CO2
	Stockholm	europe-north2	Low CO2
	Turin	europe-west12
	Warsaw	europe-central2
	Zurich	europe-west6	Low CO2
Middle East
	Doha	me-central1
	Dammam	me-central2
	Tel Aviv	me-west1
Africa
	Johannesburg	africa-south1

BigQuery partition and cluster recommender locations

TheBigQuery partitioning and clustering recommendergenerates partition or clusterrecommendations to optimize your BigQuery tables.

The partitioning and clustering recommender is available in the followingprocessing locations:

	Region description	Region name	Details
Asia Pacific
	Delhi	asia-south2
	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
Europe
	Belgium	europe-west1	Low CO2
	Berlin	europe-west10
	EU multi-region	eu
	Frankfurt	europe-west3
	London	europe-west2	Low CO2
	Netherlands	europe-west4	Low CO2
	Zürich	europe-west6	Low CO2
Americas
	Iowa	us-central1	Low CO2
	Las Vegas	us-west4
	Los Angeles	us-west2
	Montréal	northamerica-northeast1	Low CO2
	Northern Virginia	us-east4
	Oregon	us-west1	Low CO2
	Salt Lake City	us-west3
	São Paulo	southamerica-east1	Low CO2
	Toronto	northamerica-northeast2	Low CO2
	US multi-region	us

BigQuery sharing locations

BigQuery sharing (formerly Analytics Hub) is available in the following regions andmulti-regions.

Regions

The following table lists the regions in the Americas where sharing is available.

Region description	Region name	Details
Columbus, Ohio	us-east5
Dallas	us-south1	Low CO2
Iowa	us-central1	Low CO2
Las Vegas	us-west4
Los Angeles	us-west2
Mexico	northamerica-south1
Montréal	northamerica-northeast1	Low CO2
Northern Virginia	us-east4
Oklahoma	us-central2	Low CO2
Oregon	us-west1	Low CO2
Salt Lake City	us-west3
São Paulo	southamerica-east1	Low CO2
Santiago	southamerica-west1
South Carolina	us-east1
Toronto	northamerica-northeast2

The following table lists the regions in Asia Pacific where sharing is available.

Region description	Region name	Details
Delhi	asia-south2
Hong Kong	asia-east2
Jakarta	asia-southeast2
Melbourne	australia-southeast2
Mumbai	asia-south1
Osaka	asia-northeast2
Seoul	asia-northeast3
Singapore	asia-southeast1
Sydney	australia-southeast1
Taiwan	asia-east1
Tokyo	asia-northeast1

The following table lists the regions in Europe where sharing is available.

Region description	Region name	Details
Belgium	europe-west1	Low CO2
Berlin	europe-west10
Finland	europe-north1	Low CO2
Frankfurt	europe-west3
London	europe-west2	Low CO2
Madrid	europe-southwest1	Low CO2
Milan	europe-west8
Netherlands	europe-west4	Low CO2
Paris	europe-west9	Low CO2
Turin	europe-west12
Warsaw	europe-central2
Zürich	europe-west6	Low CO2

The following table lists the regions in the Middle East where sharing is available.

Region description	Region name	Details
Dammam	me-central2
Doha	me-central1
Tel Aviv	me-west1

The following table lists the regions in Africa where sharing is available.

Region description	Region name	Details
Johannesburg	africa-south1

Multi-regions

The following table lists the multi-regions where sharing is available.

Multi-region description	Multi-region name
Data centers withinmember states of the European Union1	EU
Data centers in the United States	US

¹ Data located in theEU multi-region is notstored in theeurope-west2 (London) oreurope-west6 (Zürich) datacenters.

Omni regions

The following table lists the Omni where sharing is available.

	Omni region description	Omni region name
AWS
	AWS - US East (N. Virginia)	aws-us-east-1
	AWS - US West (Oregon)	aws-us-west-2
	AWS - Asia Pacific (Seoul)	aws-ap-northeast-2
	AWS - Asia Pacific (Sydney)	aws-ap-southeast-2
	AWS - Europe (Ireland)	aws-eu-west-1
	AWS - Europe (Frankfurt)	aws-eu-central-1
Azure
	Azure - East US 2	azure-eastus2

Specify locations

When loading data, querying data, or exporting data, BigQuerydetermines the location to run the job based on the datasets referenced inthe request. For example, if a query references a table in a dataset storedin theasia-northeast1 region, the query job will run in that region.

If a query does not reference any tables or other resources contained withindatasets, and no destination table is provided, the query job will run in theUS multi-region. To ensure that BigQuery queries are stored ina specific region or multi-region, specify the location with the job request toroute the query accordingly when using the global BigQueryendpoint. If you don't specify the location, queries may be temporarily storedin BigQuery router logs when the query is used for determiningthe processing location in BigQuery.

If theproject has acapacity-based reservation in a region other than theUS and the query doesnot reference any tables or other resources contained within datasets, then youmust explicitly specify the location of the capacity-based reservation whensubmitting the job. Capacity-based commitments are tied to a location, such asUS orEU. If you run a job outside the location of your capacity, pricingfor that job automatically shifts to on-demand pricing.

You can specify the location to run a job explicitly in the following ways:

• When you query data using the Google Cloud console in the query editor,clicksettingsMore > Querysettings, expandAdvanced options, and then select yourDatalocation.
• When you write a SQL query, set the@@location system variablein the first statement of your query.
• When you use the bq command-line tool, supply the--locationglobal flag and setthe value to your location.
• When you use the API, specify your region in thelocationproperty in thejobReference section of thejob resource.

If the specified location does not match the location of every datasetinvolved in the request, including those read from and those written to, BigQuery tries to run the query as aglobal query.This declaration determines where your data is collected and processed.

Single-region locations don't match multi-region locations, even where thesingle-region location is contained within the multi-region location. Therefore,a query will be run as aglobal query if the location includes both a single-region locationand a multi-region location. For example, if a job's location is set toUS,the job will be a global query if it references a dataset inus-central1. Likewise, a jobthat references one dataset inUS and another dataset inus-central1 will be a global query. This is also true forJOIN statements with tables in both a region and a multi-region.

Dynamic queriesaren't parsed until they execute, so they can't be used to automaticallydetermine the region of a query.

Locations, reservations, and jobs

Capacity commitments are a regional resource. When you buy slots, those slotsare limited to a specific region or multi-region. If your only capacitycommitment is in theEU then you can't create a reservation in theUS. Whenyou create a reservation, you specify a location (region) and a number of slots.Those slots are pulled from your capacity commitment in that region.

Likewise, when you run a job in a region, it only uses a reservation if thelocation of the job matches the location of a reservation, unless the job is aglobal query.For example, if you assign a reservation to a project in theEU and run a query in that projecton a dataset located in theUS, then that query is not run on yourEUreservation. In the absence of anyUS reservation, the job is run ason-demand.

Location considerations

When you choose a location for your data, consider the following:

Cloud Storage

You can interact with Cloud Storage data using BigQuery in thefollowing ways:

• Query Cloud Storage data usingBigLake or non-BigLake external tables
• Load Cloud Storage data into BigQuery

Query Cloud Storage data

When you query data in Cloud Storage by using aBigLake or anon-BigLake external table,the data you query must be colocated with your BigQuery dataset,otherwise the query incursdata transfer charges.For example:

• Single region bucket: If your BigQuery dataset is in the Warsaw (europe-central2) region, the corresponding Cloud Storage bucket must also be in the Warsaw region, or any Cloud Storage dual-region that includes Warsaw.If your BigQuery dataset is in theUS multi-region,then the Cloud Storage bucket can be in the Iowa (us-central1) single region, or any dual-region that includes Iowa.Queries from any other single region incur data transfer charges, even ifthe bucket is in a location that is contained within the multi-region of the dataset.For example, if the external tables are in theUS multi-region and theCloud Storage bucket is in Oregon (us-west1), the job incursdata transfer charges.

  If your BigQuery dataset is in theEU multi-region,then the Cloud Storage bucket can be in the Netherlands (europe-west4)single region or any dual-region that includes Netherlands (europe-west4). Queries from any other single region incur data transfer fees, even if the bucket is in a location that is contained within the multi-region of the dataset. For example, if the external tables are in theEU multi-region and theCloud Storage bucket is in Warsaw (europe-central2), the job incurs data transfer charges.

• Dual-region bucket: If yourBigQuery dataset is in the Tokyo (asia-northeast1) region,the corresponding Cloud Storage bucket must be in the Tokyo region, orin a dual-region that includes Tokyo, like theASIA1 dual-region.

  If the Cloud Storage bucket is in theNAM4 dual-region or any dual-region thatincludes the Iowa(us-central1) region, the corresponding BigQuerydataset can be in theUS multi-region or in the Iowa(us-central1).

  If Cloud Storage bucket is in theEUR4 dual-region or any dual-region thatincludes the Netherlands (europe-west4) region, the corresponding BigQuerydataset can be in theEU multi-region or in the Netherlands (europe-west4).

• Multi-region bucket: Using multi-regiondataset locations with multi-region Cloud Storage buckets isnot recommended for external tables, because external query performancedepends on minimal latency and optimal network bandwidth.

  If your BigQuery dataset is in theUS multi-region, thecorresponding Cloud Storage bucket must be in a dual-region that includes Iowa (us-central1), like theNAM4dual-region, or in a custom dual-region that includes Iowa (us-central1).

  If your BigQuery dataset is in theEU multi-region, thecorresponding Cloud Storage bucket must be in a dual-region that includes Netherlands (europe-west4), like theEUR4dual-region, or in a custom dual-region that includes Netherlands (europe-west4) .

For more information about supported Cloud Storage locations, seeBucket locations in theCloud Storage documentation.

Load Cloud Storage data into BigQuery

When you load data from Cloud Storage, the data that you load must be colocatedwith your BigQuery dataset, otherwise the load job incurs data transfer charges.

For more information about load data transfer charges, see theQuery Cloud Storage datasection, as the same guidance applies to both batch loads and queries.

For more information, seeBatch loading data.

Bigtable

You must consider location when querying data fromBigtable or exporting data to Bigtable.

Query Bigtable data

When youquery data in Bigtablethrough a BigQueryexternal table,your Bigtable instance must be in the same location as yourBigQuery dataset:

• Single region: If your BigQuery dataset is in the Belgium(europe-west1) regional location, the corresponding Bigtableinstance must be in the Belgium region.
• Multi-region: Because external query performance depends on minimal latencyand optimal network bandwidth, using multi-region dataset locations isnot recommended for external tables on Bigtable.

For more information about supported Bigtable locations, seeBigtable locations.

Export data to Bigtable

• If your BigQuery dataset is in a multi-region, yourBigtable app profile must be configured to route data to a Bigtable cluster within that multi-region. For example, if your BigQuery dataset is in theUS multi-region, the Bigtable cluster can be located in theus-west1 (Oregon) region, which is within the United States.
• If your BigQuery dataset is in a single region, yourBigtable app profile must be configured to route data to a Bigtable cluster in the same region. For example, if your BigQuery dataset is in theasia-northeast1 (Tokyo) region, your Bigtable cluster must also be in theasia-northeast1 (Tokyo) region.

Google Drive

Location considerations do not apply toGoogle Driveexternal data sources.

Cloud SQL

When youquery data in Cloud SQLthrough a BigQueryfederated query,your Cloud SQL instance must be in the same location as yourBigQuery dataset.

• Single region: If your BigQuery dataset is in the Belgium (europe-west1) regional location, the corresponding Cloud SQL instance must be in the Belgium region.
• Multi-region: If your BigQuery dataset is in theUS multi-region, the corresponding Cloud SQL instance must be in a single region in the US geographic area.

For more information about supported Cloud SQL locations, seeCloud SQL locations.

Spanner

When youquery data in Spannerthrough a BigQueryfederated query,your Spanner instance must be in the same location as yourBigQuery dataset.

• Single region: If your BigQuery dataset is in the Belgium(europe-west1) regional location, the corresponding Spannerinstance must be in the Belgium region.
• Multi-region: If your BigQuery dataset is in theUSmulti-region, the corresponding Spanner instance must be in asingle region in the US geographic area.

For more information about supported Spanner locations, seeSpanner locations.

Analysis tools

Colocate your BigQuery dataset with youranalysis tools:

• Dataproc: When you query BigQuery datasets using a BigQuery connector, your BigQuery dataset should be colocated with your Dataproc cluster.
Dataproc is supported in all Compute Engine locations.
• Vertex AI Workbench: When you query BigQuery datasets using Jupyter notebooks in Vertex AI Workbench, your BigQuery dataset should be colocated with your Vertex AI Workbench instance.
View thesupported Vertex AI Workbench locations.

Data management plans

Develop a data management plan:

• If you choose a regional storage resource such as a BigQuery dataset or a Cloud Storage bucket, develop a plan forgeographically managing your data.

Restrict locations

You can restrict the locations in which your datasets can be created by usingtheOrganization Policy Service.For more information, seeRestricting resourcelocations andResource locations supportedservices.

Dataset security

To control access to datasets in BigQuery, seeControlling access to datasets.For information about data encryption, seeEncryption at rest.

What's next

• Learn how tocreate datasets.
• Learn aboutloading data into BigQuery.
• Learn about BigQuerypricing.
• Learn aboutglobal queries.
• View all the Google Cloud services available in locations worldwide.
• Explore additional location-based concepts, such as zones, that applyto other Google Cloud services.