You specify a location for storing your Cloud Healthcare API data when
you create a dataset. After you create the dataset, the location cannot be
changed. Data within the dataset is stored at rest in the chosen location.
The location is tied to the dataset's identity and is a permanent part of the
dataset's resource name.
All data stores within the dataset are assigned to the same region as the
dataset.
There are two types of locations:
A regional location is a specific geographic place, such as Tokyo.
For more information, see Regional resources
on the Geography and Regions page.
A multi-regional location is a large geographic area, such as the United
States, that contains at least two regional locations. For more information,
see Multi-regional resources
on the Geography and Regions page.
Data centers within member states of the European Union
Location quota requests
You can request a quota increase for the Cloud Healthcare API in a specific
region, or in a multi-region location.
To request a quota increase in a single region: In your quota increase request,
specify the region.
To request a quota increase in a multi-region location:
For a quota increase in the us multi-region, state in your request that the quota is for "US meta region."
For a quota increase in the eu multi-region, state in your request that the quota is for "EU meta region."
Location considerations
When you choose a location for your data, you might want to consider factors
such as:
Regulatory requirements about where to store your data
Latency
Resiliency
Cost
Colocation with other Google Cloud services
For example,
Google manages multi-regional locations
to be redundant and distributed within and
across regions. These services optimize availability, performance, and
resource efficiency. As a result, these services require a trade-off on either
latency or the consistency model.
Consider doing the following when choosing a location for your data:
Colocate your dataset and your external data source.
Colocate your dataset with your Cloud Storage buckets when importing data.
Colocate your dataset with your Cloud Storage buckets and BigQuery datasets when exporting data.
Moving Cloud Healthcare API data between locations
You cannot change the location of a dataset after it is created. Also, you
cannot move a dataset from one location to another. If you need to move data
from one location to another, complete one of the following processes:
FHIR data
Export
the data from your FHIR stores to a regional or multi-regional
Cloud Storage bucket. When you export the data, the operation only exports
the current version of each resource. The operation does not export version
history; there is no bulk export operation for version history.
There are charges for exporting
FHIR data to Cloud Storage. You also incur charges for
storing the exported data
in Cloud Storage.
After you transfer the data to a Cloud Storage bucket,
create a new dataset in the new location. Create any FHIR stores in the new
dataset that you require for storing your data. Then, import
your data from Cloud Storage into the new FHIR stores.
DICOM data
Export
the data from your DICOM stores to a regional or multi-regional
Cloud Storage bucket.
There are charges for exporting
DICOM data to Cloud Storage. You also incur charges for
storing the exported data
in Cloud Storage.
After you transfer the data to a Cloud Storage bucket,
create a new dataset in the new location. Create any DICOM stores in the new
dataset that you require for storing your data. Then, import
your data from Cloud Storage into the new DICOM stores.
HL7v2 data
Export the HL7v2 messages
from your HL7v2 store to a regional or multi-regional
Cloud Storage bucket.
There are charges for exporting
HL7v2 messages to Cloud Storage. You also incur charges for
storing the exported data
in Cloud Storage.
After you transfer the data to a Cloud Storage bucket,
create a new dataset in the new location. Create any HL7v2 stores in the new
dataset that you require for storing your data. Then, import
your messages from Cloud Storage into the new HL7v2 stores.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eGoogle Cloud Healthcare API data is stored in either a regional location, which is a specific geographic place, or a multi-regional location, a large geographic area with at least two regional locations.\u003c/p\u003e\n"],["\u003cp\u003eWhen creating a dataset in the Cloud Healthcare API, you must specify a location, which becomes a permanent part of the dataset's identity and cannot be changed after creation.\u003c/p\u003e\n"],["\u003cp\u003eThe Cloud Healthcare API supports a subset of Google Cloud locations, and there are numerous options within Americas, Asia Pacific, Europe, and Middle East regional locations, along with 'us' and 'eu' as multi-regional locations.\u003c/p\u003e\n"],["\u003cp\u003eMoving Cloud Healthcare API data between locations requires exporting the data to Cloud Storage and then importing it into a newly created dataset and corresponding stores in the desired location.\u003c/p\u003e\n"],["\u003cp\u003eFactors such as regulatory requirements, latency, resiliency, cost, and colocation with other Google Cloud services should be considered when choosing a location for your Cloud Healthcare API data.\u003c/p\u003e\n"]]],[],null,["# Regions\n\nGoogle Cloud uses [regions, subdivided into zones](/docs/geography-and-regions#regions_and_zones),\nto define the geographic location of physical computing resources.\n\nKey concepts\n------------\n\nYou specify a location for storing your Cloud Healthcare API data when\nyou create a dataset. After you create the dataset, the location cannot be\nchanged. Data within the dataset is stored at rest in the chosen location.\n\nThe location is tied to the dataset's identity and is a permanent part of the\ndataset's [resource name](/healthcare-api/docs/concepts/api-structure#resource_names).\nAll data stores within the dataset are assigned to the same region as the\ndataset.\n\nThere are two types of locations:\n\n- A *regional location* is a specific geographic place, such as Tokyo.\n For more information, see [Regional resources](/docs/geography-and-regions#regional_resources)\n on the Geography and Regions page.\n\n- A *multi-regional location* is a large geographic area, such as the United\n States, that contains at least two regional locations. For more information,\n see [Multi-regional resources](/docs/geography-and-regions#multiregional_resources)\n on the Geography and Regions page.\n\nAvailable regions\n-----------------\n\nThe Cloud Healthcare API supports a subset of the\n[full list of Google Cloud locations](https://cloud.google.com/about/locations).\n\nThe Cloud Healthcare API is available in the following regions:\n\n### Regional locations\n\n### Multi-regional locations\n\nLocation quota requests\n-----------------------\n\nYou can request a quota increase for the Cloud Healthcare API in a specific\n[region](/healthcare-api/docs/regions), or in a [multi-region location](/healthcare-api/docs/regions#multi-regional_locations).\n\nTo request a quota increase in a single region: In your quota increase request,\nspecify the region.\n\nTo request a quota increase in a multi-region location:\n\n- For a quota increase in the `us` multi-region, state in your request that the quota is for \"US meta region.\"\n- For a quota increase in the `eu` multi-region, state in your request that the quota is for \"EU meta region.\"\n\nLocation considerations\n-----------------------\n\nWhen you choose a location for your data, you might want to consider factors\nsuch as:\n\n- Regulatory requirements about where to store your data\n- Latency\n- Resiliency\n- Cost\n- Colocation with other Google Cloud services\n\nFor example,\nGoogle manages [multi-regional locations](/docs/geography-and-regions#multi-regional_resources)\nto be redundant and distributed within and\nacross regions. These services optimize availability, performance, and\nresource efficiency. As a result, these services require a trade-off on either\nlatency or the consistency model.\n\nConsider doing the following when choosing a location for your data:\n\n- **Colocate your dataset and your external data source**.\n\n- **Colocate your dataset with your Cloud Storage buckets when importing data**.\n\n- **Colocate your dataset with your Cloud Storage buckets and BigQuery datasets when exporting data**.\n\nMoving Cloud Healthcare API data between locations\n--------------------------------------------------\n\nYou cannot change the location of a dataset after it is created. Also, you\ncannot move a dataset from one location to another. If you need to move data\nfrom one location to another, complete one of the following processes:\n\n### FHIR data\n\n1. [Export](/healthcare-api/docs/how-tos/fhir-import-export#exporting_fhir_resources)\n the data from your FHIR stores to a regional or multi-regional\n Cloud Storage bucket. When you export the data, the operation only exports\n the current version of each resource. The operation does not export version\n history; there is no bulk export operation for version history.\n\n There are [charges](https://cloud.google.com/healthcare-api/pricing#etl_operations) for exporting\n FHIR data to Cloud Storage. You also incur charges for\n [storing the exported data](/storage/pricing#storage-pricing)\n in Cloud Storage.\n2. After you transfer the data to a Cloud Storage bucket,\n create a new dataset in the new location. Create any FHIR stores in the new\n dataset that you require for storing your data. Then, [import](/healthcare-api/docs/how-tos/fhir-import-export#importing_fhir_resources)\n your data from Cloud Storage into the new FHIR stores.\n\n### DICOM data\n\n1. [Export](/healthcare-api/docs/how-tos/dicom-import-export#exporting_dicom_instances)\n the data from your DICOM stores to a regional or multi-regional\n Cloud Storage bucket.\n\n There are [charges](https://cloud.google.com/healthcare-api/pricing#etl_operations) for exporting\n DICOM data to Cloud Storage. You also incur charges for\n [storing the exported data](/storage/pricing#storage-pricing)\n in Cloud Storage.\n2. After you transfer the data to a Cloud Storage bucket,\n create a new dataset in the new location. Create any DICOM stores in the new\n dataset that you require for storing your data. Then, [import](/healthcare-api/docs/how-tos/dicom-import-export#importing_dicom_objects)\n your data from Cloud Storage into the new DICOM stores.\n\n### HL7v2 data\n\n1. [Export the HL7v2 messages](/healthcare-api/docs/how-tos/hl7v2-import-export#exporting_hl7v2_messages)\n from your HL7v2 store to a regional or multi-regional\n Cloud Storage bucket.\n\n There are [charges](https://cloud.google.com/healthcare-api/pricing#etl_operations) for exporting\n HL7v2 messages to Cloud Storage. You also incur charges for\n [storing the exported data](/storage/pricing#storage-pricing)\n in Cloud Storage.\n2. After you transfer the data to a Cloud Storage bucket,\n create a new dataset in the new location. Create any HL7v2 stores in the new\n dataset that you require for storing your data. Then, [import](/healthcare-api/docs/how-tos/hl7v2-import-export)\n your messages from Cloud Storage into the new HL7v2 stores."]]
