When you create a Knowledge Catalog (formerly Dataplex Universal Catalog) resource such as a lake, zone, or
asset, you select the region where it is stored and accessed. To reduce latency
and increase availability, you typically store resources close to the users and
services that need them.

An asset's attached data source, either a Cloud Storage bucket
or BigQuery dataset, can be configured as multi-region. This
determines how data is replicated and priced. For details, see
[Cloud Storage bucket locations](https://docs.cloud.google.com/storage/docs/locations) and
[BigQuery dataset replication](https://docs.cloud.google.com/bigquery/docs/data-replication).

A Knowledge Catalog asset bucket is physically located in the same region
as its lake. For example, you can have a lake in `us-west1` and zone in
`Multi-region (US)` for an asset bucket in `Multi-region (US)`. Although the
zone and asset bucket support multi-region operation, they are still physically
located in `us-west1`.

For more information about how Knowledge Catalog handles multi-region
assets, see [Regional resources](https://docs.cloud.google.com/dataplex/docs/regional-resources).

## Regions

The following table lists the regions where Knowledge Catalog is available.
Regions are added regularly. For updates, check the [Knowledge Catalog
release notes](https://docs.cloud.google.com/dataplex/docs/release-notes).

| Region name | Region description | Data lineage available |
|---|---|---|
| `asia-east1` | Taiwan | Yes |
| `asia-east2` | Hong Kong | Yes |
| `asia-northeast1` | Tokyo | Yes |
| `asia-northeast2` | Osaka | Yes |
| `asia-northeast3` | Seoul | Yes |
| `asia-south1` | Mumbai | Yes |
| `asia-south2` | Delhi | Yes |
| `asia-southeast1` | Singapore | Yes |
| `asia-southeast2` | Jakarta | Yes |
| `africa-south1` | Johannesburg | Yes |
| `australia-southeast1` | Sydney | Yes |
| `australia-southeast2` | Melbourne | Yes |
| `europe-central2` | Warsaw | Yes |
| `europe-north1` | Finland | Yes |
| `europe-north2` | Stockholm | Yes |
| `europe-southwest1` | Madrid | Yes |
| `europe-west1` | Belgium | Yes |
| `europe-west2` | London | Yes |
| `europe-west3` | Frankfurt | Yes |
| `europe-west4` | Netherlands | Yes |
| `europe-west6` | Zurich | Yes |
| `europe-west8` | Milan | Yes |
| `europe-west9` | Paris | Yes |
| `europe-west10` | Berlin | Yes |
| `europe-west12` | Turin | Yes |
| `me-central1` | Doha | Yes |
| `me-central2` | Dammam | Yes |
| `me-west1` | Tel Aviv | Yes |
| `northamerica-northeast1` | Montreal | Yes |
| `northamerica-northeast2` | Toronto | Yes |
| `northamerica-south1` | Mexico | Yes |
| `southamerica-east1` | Sao Paulo | Yes |
| `southamerica-west1` | Santiago | Yes |
| `us-central1` | Iowa | Yes |
| `us-east1` | South Carolina | Yes |
| `us-east4` | Northern Virginia | Yes |
| `us-east5` | Columbus | Yes |
| `us-south1` | Dallas | Yes |
| `us-west1` | Oregon | Yes |
| `us-west2` | Los Angeles | Yes |
| `us-west3` | Salt Lake City | Yes |
| `us-west4` | Las Vegas | Yes |

### BigQuery Omni regions for data lineage

Data lineage is available in the following
[BigQuery Omni regions](https://docs.cloud.google.com/bigquery/docs/omni-introduction):

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

## What's next

- Learn more about [Geography and regions](https://docs.cloud.google.com/docs/geography-and-regions) in Google Cloud.
- See the full list of [Google Cloud locations](https://cloud.google.com/about/locations/).