# Introduction to BigQuery sharing

BigQuery sharing (formerly Analytics Hub) is a data exchange platform that
lets you securely share, discover, and access data across organizational
boundaries without replicating data.

You can use BigQuery sharing to discover curated third-party and
Google datasets, and combine them with your internal data to augment analytics
and machine learning initiatives.

BigQuery sharing Identity and Access Management (IAM) roles let you perform
the following BigQuery sharing tasks:

- [Analytics Hub Publisher](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles#ah-publisher-role)
  (`roles/analyticshub.publisher`): share data with your partner network or within
  your own organization in real time. [Listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-introduction#listings) let you share data
  without replicating data, and you can monetize listings on
  [Google Cloud Marketplace](https://docs.cloud.google.com/bigquery/docs/analytics-hub-cloud-marketplace) or
  through your own channels. You can build a catalog of analytics-ready data
  sources with granular permissions that let you deliver data to authorized
  subscribers. You can also manage subscriptions and view the usage metrics for
  your listings.

- [Analytics Hub Subscriber](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles#ah-subscriber-role)
  (`roles/analyticshub.subscriber`): discover data, combine shared data with
  your existing data, and use the
  [built-in features of BigQuery](https://docs.cloud.google.com/bigquery/docs/introduction#explore-bigquery).
  When you subscribe to a listing, a [linked dataset](https://docs.cloud.google.com/bigquery/docs/analytics-hub-introduction#linked_datasets) or
  linked Pub/Sub subscription is created in your Google Cloud project.
  To manage your subscriptions, use the
  [Subscription resource](https://docs.cloud.google.com/bigquery/docs/reference/analytics-hub/rest/v1/projects.locations.subscriptions),
  which stores information about the subscriber and represents the connection
  between publisher and subscriber.

- [Analytics Hub Viewer](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles#ah-subscriber-role)
  (`roles/analyticshub.viewer`): browse the data exchanges and listings that you
  have access to view in BigQuery sharing. If you don't have subscription
  permissions to listings, then you can request permission from the publisher to
  access the shared data. You can discover
  Cloud Marketplace-integrated commercial listings on both
  BigQuery sharing and Cloud Marketplace.

- [Analytics Hub Admin](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles#ah-admin-role)
  (`roles/analyticshub.admin`): create [data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-introduction#data_exchanges) that let
  publishers share data, and grant permissions to data publishers and
  subscribers to access these data exchanges.

For more information, see
[Configure Analytics Hub roles](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles).

## Architecture

BigQuery sharing is built on a publish and subscribe model of
Google Cloud data resources, which lets you share data in place without
replication. BigQuery sharing supports the following resources:

- BigQuery datasets
- Pub/Sub topics

### Publisher workflow

In the publisher workflow, you create shared resources in your project,
organize them into listings within a data exchange, and grant access to
subscribers:

![The workflow for the Analytics Hub Publisher role, which includes shared resources, data exchanges, and listings.](https://docs.cloud.google.com/static/bigquery/images/analytics-hub-publisher-workflow.svg)

The following sections describe the components in the publisher workflow.

#### Shared datasets

A shared dataset is a BigQuery dataset that serves as the unit of
data sharing in BigQuery sharing. The separation of compute and storage
in the BigQuery architecture lets data publishers share datasets
with multiple subscribers without replicating data. As a publisher, you create
or use an existing BigQuery dataset in your project with the
following supported objects:

- [Authorized views](https://docs.cloud.google.com/bigquery/docs/authorized-views)
- [Authorized datasets](https://docs.cloud.google.com/bigquery/docs/authorized-datasets)
- [BigQuery ML models](https://docs.cloud.google.com/bigquery/docs/bqml-introduction)
- [External tables](https://docs.cloud.google.com/bigquery/docs/external-tables)
- [Materialized views](https://docs.cloud.google.com/bigquery/docs/materialized-views-intro)
- [Routines](https://docs.cloud.google.com/bigquery/docs/routines)

  - [User-defined functions (UDFs)](https://docs.cloud.google.com/bigquery/docs/user-defined-functions)
  - [Table functions](https://docs.cloud.google.com/bigquery/docs/table-functions)
  - [SQL stored procedures](https://docs.cloud.google.com/bigquery/docs/procedures)
- [Tables](https://docs.cloud.google.com/bigquery/docs/tables-intro)

- [Table snapshots](https://docs.cloud.google.com/bigquery/docs/table-snapshots-intro)

- [Views](https://docs.cloud.google.com/bigquery/docs/views-intro)

Shared datasets support
[column-level security](https://docs.cloud.google.com/bigquery/docs/column-level-security-intro)
and
[row-level security](https://docs.cloud.google.com/bigquery/docs/row-level-security-intro).

#### Shared topics

A shared topic is a [Pub/Sub topic](https://docs.cloud.google.com/pubsub/docs/create-topic),
which is the unit of
[streaming data sharing in BigQuery](https://docs.cloud.google.com/bigquery/docs/analytics-hub-stream-sharing).
As a publisher, you create or use an existing Pub/Sub topic in
your project and distribute it to your subscribers.

#### Data exchanges

A data exchange is a container that lets publishers share data listings and
lets subscribers browse and request access directly. It contains listings
that reference shared resources. Publishers and administrators can grant access
to subscribers at the exchange and listing level, which avoids explicitly
granting access on the underlying shared resources. When you
[create a data exchange](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-exchanges#create-exchange),
you can assign a primary contact email address so that subscribers can contact
the data exchange owner.

A data exchange can be one of the following types:

- **Private data exchange**: by default, a data exchange is private. Only users or groups that have access to that exchange can view or subscribe to its listings.
- **Public data exchange** : a public data exchange lets all [Google Cloud users (`allAuthenticatedUsers`)](https://docs.cloud.google.com/iam/docs/principals-overview#all-authenticated-users) [discover](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings#discover-listings) and [subscribe to](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings#subscribe-listings) its listings. For more information, see [Make a data exchange public](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-exchanges#make-data-exchange-public).

The Analytics Hub Admin role lets you create multiple data exchanges and manage
team members who perform BigQuery sharing tasks.

#### Listings

A listing is a reference to a shared resource that a publisher lists in a data
exchange. As a publisher, you can create a listing and specify the resource
description, sample queries, sample message data, documentation links, and
relevant instructions for subscribers. When you create a listing, you can
assign a primary contact email address, provider details, and publisher details.
For more information, see
[Manage listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-listings).

A listing can be one of the following types, based on the
IAM policy set for the listing and its parent data exchange:

- **Private listing**: by default, a listing is private and shared directly with specific users or groups. For example, a private listing can reference internal metrics datasets that you share with specific teams within your organization.
- **Public listing** : shared with all [Google Cloud users (`allAuthenticatedUsers`)](https://docs.cloud.google.com/iam/docs/principals-overview#all-authenticated-users). Listings in a public data exchange are public listings. These listings can reference free public resources or commercial resources. If the listing is for a commercial resource, subscribers can request access directly from the data provider or purchase [Cloud Marketplace-integrated commercial listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-cloud-marketplace).

#### Data egress options

For BigQuery shared datasets, data egress options let publishers
restrict subscribers from exporting data out of linked datasets.

Publishers can enable data egress restrictions on a listing, query results, or
both. When data egress is restricted, the following restrictions apply:

- Copy, clone, export, and snapshot APIs are unavailable.
- Copy, clone, export, and snapshot options are unavailable in the Google Cloud console.
- BigQuery Data Transfer Service is unavailable on the restricted dataset.
- [`CREATE TABLE AS SELECT` statements](https://docs.cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) and [writing to a destination table](https://docs.cloud.google.com/bigquery/docs/writing-results) are unavailable.
- [`CREATE VIEW AS SELECT` statements](https://docs.cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) and writing to a destination view are unavailable.

When you
[create a listing](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-listings#create_a_listing),
you can set the appropriate data egress options.

### Subscriber workflow

In the subscriber workflow, you browse data exchanges to discover listings,
subscribe to listings, and query the linked resources in your project:

![The workflow for the Analytics Hub Subscriber role, which includes shared resources, data exchanges, listings, and linked resources.](https://docs.cloud.google.com/static/bigquery/images/analytics-hub-subscriber-workflow.svg)

The following sections describe the components in the subscriber workflow.

#### Linked datasets

A linked dataset is a read-only BigQuery dataset that serves as
a pointer or reference to a shared dataset. Subscribing to a listing creates a
linked dataset in your project without replicating data. Subscribers can query
standard tables and views in real time, but they can't add or update objects in
the dataset.

Linked datasets are authorized to access tables and views in a shared dataset
without requiring additional IAM authorization on the underlying
source dataset. In addition to standard tables and views, linked datasets
support the following authorized resources:

- [Authorized views](https://docs.cloud.google.com/bigquery/docs/authorized-views)
- [Authorized datasets](https://docs.cloud.google.com/bigquery/docs/authorized-datasets)
- [Authorized routines](https://docs.cloud.google.com/bigquery/docs/authorized-routines)

For more information about linked datasets, see
[View and subscribe to listings and data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings).

#### Linked Pub/Sub subscriptions

Subscribing to a listing with a shared topic creates a linked
Pub/Sub subscription in the subscriber project without duplicating
the shared topic or message data. Subscribers of the
[linked Pub/Sub subscription](https://docs.cloud.google.com/pubsub/docs/subscription-overview)
can access messages published to the shared topic without additional
IAM authorization on the source topic. Publishers can manage
subscriptions directly in Pub/Sub or through
BigQuery sharing subscription management.

For more information about linked Pub/Sub subscriptions, see
[Stream sharing with Pub/Sub](https://docs.cloud.google.com/bigquery/docs/analytics-hub-stream-sharing).

## Example use cases

This section provides examples of how to use BigQuery sharing for
partner collaboration and data monetization.

### Partner collaboration

Suppose you're a retailer and your organization maintains real-time demand
forecasting data in a Google Cloud project named `Forecasting`.
You want to share this demand forecasting data with hundreds of vendors in
your supply-chain network. The following sections describe how to share data
across roles.

#### Administrators

As the owner of the `Forecasting` project, you enable the Analytics Hub API and
grant the Analytics Hub Admin role (`roles/analyticshub.admin`) to a team member
who administers the data exchange. Principals with this role are
*BigQuery sharing administrators*.

A BigQuery sharing administrator can perform the following tasks:

- Create, update, delete, and share the data exchange in your organization's `Forecasting` project.
- Manage other BigQuery sharing administrators with the Analytics Hub Admin role.
- Manage BigQuery sharing publishers by granting the [Analytics Hub Publisher role](https://docs.cloud.google.com/bigquery/docs/access-control#analyticshub.publisher) (`roles/analyticshub.publisher`) to employees. If employees only need to update, delete, and share listings without creating them, grant the [Analytics Hub Listing Admin role](https://docs.cloud.google.com/bigquery/docs/access-control#analyticshub.listingAdmin) (`roles/analyticshub.listingAdmin`).
- Manage BigQuery sharing subscribers by granting the [Analytics Hub Subscriber role](https://docs.cloud.google.com/bigquery/docs/access-control#analyticshub.subscriber) (`roles/analyticshub.subscriber`) to a Google group consisting of all vendors. If vendors only need to view available exchanges and listings without subscribing, grant the [Analytics Hub Viewer role](https://docs.cloud.google.com/bigquery/docs/access-control#analyticshub.viewer) (`roles/analyticshub.viewer`).

For more information, see
[BigQuery sharing IAM roles](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles#user_roles)
and
[Manage data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-exchanges).

#### Publishers

In this scenario, data publishers package supply-chain datasets into separate
listings to serve vendor needs. Publishers create the following listings in the
`Forecasting` project:

- Listing A: Demand Forecast Dataset 1
- Listing B: Demand Forecast Dataset 2
- Listing C: Demand Forecast Dataset 3

Publishers can
[track usage metrics](https://docs.cloud.google.com/bigquery/docs/analytics-hub-monitor-listings#use-analytics-hub)
for their shared datasets, including the following details:

- Jobs that run against the shared dataset.
- Consumption details by subscriber projects and organizations.
- Total rows and bytes processed.

For more information, see
[Manage listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-listings).

#### Subscribers

Subscribers browse listings that they have access to in data exchanges. Vendors
subscribe to these listings to add datasets to their projects as linked
datasets. Vendors can then run queries on these linked datasets and retrieve
forecasting results in real time.

For more information, see
[View and subscribe to listings and data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings).

### Data monetization

Suppose you're a financial data provider with curated historical equity pricing
datasets in a Google Cloud project named `MarketDataSource`. You want to
monetize this data by offering it to external financial institutions and
traders. The following sections describe how to monetize data through
BigQuery sharing.

#### Administrators

As the owner of the `MarketDataSource` project, you enable the Analytics Hub API
and Cloud Marketplace API, and then grant the Analytics Hub Admin role
(`roles/analyticshub.admin`) to the team managing the commercial exchange.
Principals with this role are *BigQuery sharing administrators*.

A BigQuery sharing administrator can perform the following tasks:

- Create a public data exchange and [integrate it with Cloud Marketplace](https://docs.cloud.google.com/bigquery/docs/analytics-hub-cloud-marketplace).
- Manage BigQuery sharing publishers by granting the Analytics Hub Publisher role (`roles/analyticshub.publisher`) to data engineers responsible for creating commercial listings. If employees only need to update, delete, and share listings without creating them, grant the Analytics Hub Listing Admin role (`roles/analyticshub.listingAdmin`).
- Manage commercial terms and pricing models in Cloud Marketplace.

For more information, see
[Manage data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-exchanges)
and
[Cloud Marketplace-integrated commercial listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-cloud-marketplace).

#### Publishers

In this scenario, publishers package financial data products into tiered
listings based on subscription models. Publishers create the following listings:

- Listing A: Global Equity Prices (Monthly Subscription)
- Listing B: Real-time Market Signals (Annual Subscription)
- Listing C: Historical Economic Indicators (Free Trial)

Publishers can
[track usage metrics](https://docs.cloud.google.com/bigquery/docs/analytics-hub-monitor-listings#use-analytics-hub)
for their shared datasets, including the following details:

- Jobs that run against the shared dataset.
- Consumption details by subscriber projects and organizations.
- Total rows and bytes processed.

For more information, see
[Manage listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-listings).

#### Subscribers

Subscribers browse listings in BigQuery sharing or directly in
Cloud Marketplace. After purchasing a subscription, subscribers create
a linked dataset in their Google Cloud project and query historical data
alongside proprietary trading models without manual data ingestion or file
replication.

For more information, see
[View and subscribe to listings and data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings).

## Pricing

There's no additional cost for managing data exchanges or listings in
BigQuery sharing.

The following table summarizes the pricing models for supported resources:

| Resource | Publisher costs | Subscriber costs | More information |
|---|---|---|---|
| **BigQuery datasets** | Data storage | Queries run against the shared data (on-demand or capacity pricing) | [BigQuery pricing](https://cloud.google.com/bigquery/pricing) |
| **Pub/Sub topics** | Data written (publish throughput) and network egress (if applicable) | Data read (subscribe throughput) and network egress (if applicable) | [Pub/Sub pricing](https://cloud.google.com/pubsub/pricing#pubsub) |

## Supported regions

BigQuery sharing is supported in the following regions and
multi-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` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Iowa | `us-central1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Las Vegas | `us-west4` |   |
| Los Angeles | `us-west2` |   |
| Mexico | `northamerica-south1` |   |
| Montréal | `northamerica-northeast1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Northern Virginia | `us-east4` |   |
| Oklahoma | `us-central2` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Oregon | `us-west1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Salt Lake City | `us-west3` |   |
| São Paulo | `southamerica-east1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| 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` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Berlin | `europe-west10` |   |
| Finland | `europe-north1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Frankfurt | `europe-west3` |   |
| London | `europe-west2` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Madrid | `europe-southwest1` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Milan | `europe-west8` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Netherlands | `europe-west4` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Paris | `europe-west9` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Turin | `europe-west12` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Warsaw | `europe-central2` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |
| Zürich | `europe-west6` | ![leaf icon](https://cloud.google.com/sustainability/region-carbon/gleaf.svg) [Low CO~2~](https://cloud.google.com/sustainability/region-carbon#region-picker) |

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 within [member states](https://europa.eu/european-union/about-eu/countries_en) 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.

#### 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` |

## Quotas

For information about BigQuery sharing resource quotas and limits, see
[Quotas and limits](https://docs.cloud.google.com/bigquery/quotas#analytics-hub).

## Compliance

BigQuery sharing, as part of BigQuery, complies with the
following compliance programs:

- [ISO 27001](https://cloud.google.com/security/compliance/services-in-scope)
- [ISO 27017](https://cloud.google.com/security/compliance/services-in-scope)
- [ISO 27018](https://cloud.google.com/security/compliance/services-in-scope)
- [SOC 1](https://cloud.google.com/security/compliance/services-in-scope)
- [SOC 2](https://cloud.google.com/security/compliance/services-in-scope)
- [SOC 3](https://cloud.google.com/security/compliance/services-in-scope)
- [PCI DSS](https://cloud.google.com/security/compliance/services-in-scope)
- [Penetration Testing](https://cloud.google.com/security/compliance/services-in-scope)
- [HIPAA](https://cloud.google.com/security/compliance/hipaa)
- [HITRUST](https://cloud.google.com/security/compliance/hitrust)

## Limitations

The following sections describe the operational and interoperability
limitations for BigQuery sharing.

### General resource limitations

The following general resource limitations apply to BigQuery sharing:

- A shared dataset can have a maximum of 1,000 linked datasets.
- A shared topic can have a [maximum](https://docs.cloud.google.com/pubsub/quotas#resource_limits) of 10,000 Pub/Sub subscriptions. This limit includes linked Pub/Sub subscriptions and subscriptions created directly in Pub/Sub.
- A dataset with unsupported resources can't be selected as a shared dataset. For supported objects, see [Shared datasets](https://docs.cloud.google.com/bigquery/docs/analytics-hub-introduction#shared_datasets).
- You can't set [IAM roles](https://docs.cloud.google.com/bigquery/docs/access-control) or [IAM policies](https://docs.cloud.google.com/config-connector/docs/reference/resource-docs/iam/iampolicy) on individual tables within a linked dataset. Apply them at the linked dataset level instead.
- You can't attach [IAM tags](https://docs.cloud.google.com/bigquery/docs/tags) to tables within a linked dataset. Apply them at the linked dataset level instead.
- Linked datasets created before July 25, 2023, aren't backfilled by the [Subscription resource](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-subscriptions). Only subscriptions created after July 25, 2023, work with the API methods.

### Publisher limitations

If you're a publisher, the following BigQuery interoperability
limitations apply:

- You must grant subscribers explicit permissions to read the source dataset to query views within linked datasets. As a best practice, create [authorized views](https://docs.cloud.google.com/bigquery/docs/authorized-views) to grant subscribers access to view data without granting access to underlying source data.
- The [query plan](https://docs.cloud.google.com/bigquery/docs/query-plan-explanation) reveals the shared view query and routine query definitions, including project IDs and other datasets involved in authorized views. Don't include sensitive information, such as encryption keys, in the shared view or routine query.
- Shared datasets are indexed in [Knowledge Catalog](https://docs.cloud.google.com/knowledge-catalog/docs/metadata-overview). Schema updates on a shared dataset become available to subscribers immediately. However, when there are more than 100 subscribers or tables in a shared dataset, updates might require up to 18 hours to index. Due to the indexing delay, subscribers can't search for updated resources in the Google Cloud console immediately.
- Shared topics are indexed in Knowledge Catalog, but you can't filter specifically for their resource type.
- If you configure [row-level security](https://docs.cloud.google.com/bigquery/docs/row-level-security-intro), [column-level access control](https://docs.cloud.google.com/bigquery/docs/column-level-security-intro), or [data masking](https://docs.cloud.google.com/bigquery/docs/column-data-masking-intro) policies on listed tables, or on base tables referenced by shared authorized views, subscribers can't query the linked dataset from a Standard edition reservation. Subscribers must run query jobs by using the on-demand pricing model or an Enterprise or Enterprise Plus edition reservation. In a Standard edition reservation, a query is rejected even if it references only unprotected columns of a table with policy tags. For more information about editions, see [Introduction to BigQuery editions](https://docs.cloud.google.com/bigquery/docs/editions-intro).

### Subscriber limitations

If you're a subscriber, the following BigQuery interoperability
limitations apply:

- Materialized views that refer to tables in the linked dataset aren't supported.
- Taking [snapshots](https://docs.cloud.google.com/bigquery/docs/table-snapshots-intro) of linked dataset tables isn't supported.
- Queries with linked datasets and `JOIN` statements that exceed 1 TB (physical storage) might fail. If you encounter this issue, [contact support](https://docs.cloud.google.com/bigquery/docs/getting-support).
- You can't use [region qualifiers](https://docs.cloud.google.com/bigquery/docs/information-schema-intro#region_qualifier) with `INFORMATION_SCHEMA` views to [view metadata for your linked dataset](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings#view-table-metadata).

### Multi-region listing limitations

The following limitations apply to listings spanning multiple regions:

- Listings for multiple regions are supported only for shared datasets and linked dataset replicas. Listings for multiple regions aren't supported for shared Pub/Sub topics or subscriptions.
- Listings for multiple regions aren't supported in data clean rooms.
- Listings for multiple regions aren't supported in [BigQuery Omni regions](https://docs.cloud.google.com/bigquery/docs/omni-introduction#locations).

### Usage metrics limitations

The following limitations apply to usage metrics:

- You can't get usage metrics for listings subscribed before July 20, 2023.
- [External table](https://docs.cloud.google.com/bigquery/docs/external-tables) usage metrics for the `num_rows_processed` and `total_bytes_processed` fields might contain inaccurate data.
- Consumption usage metrics are supported only for usage with
  [BigQuery jobs](https://docs.cloud.google.com/bigquery/docs/managing-jobs). The following
  resources don't support consumption metrics:

  - [BigQuery Storage Read API](https://docs.cloud.google.com/bigquery/docs/reference/storage#read_from_a_session_stream)
  - [`tabledata.list`](https://docs.cloud.google.com/bigquery/docs/reference/rest/v2/tabledata/list)
  - [BigQuery BI Engine queries](https://docs.cloud.google.com/bigquery/docs/bi-engine-intro)
- Usage metrics for [views](https://docs.cloud.google.com/bigquery/docs/views-intro) are populated only for
  queries after April 22, 2024.

- Usage metrics aren't captured for linked Pub/Sub subscriptions
  in BigQuery. You can view usage directly in
  Pub/Sub.

- SQL stored procedures aren't available in the BigQuery sharing usage
  metrics dashboard. You can view details in the `INFORMATION_SCHEMA.ROUTINES`
  view, but not in the `INFORMATION_SCHEMA.SHARED_DATASET_USAGE` view. For more
  information, see
  [Use `INFORMATION_SCHEMA` views](https://docs.cloud.google.com/bigquery/docs/analytics-hub-monitor-listings#use-information-schema).

### VPC Service Controls and Salesforce Data 360 limitations

The following limitations apply to VPC Service Controls and
Salesforce Data 360:

- Don't publish shared data or host data exchanges in projects inside VPC Service Controls perimeters unless you configure appropriate [ingress and egress rules](https://docs.cloud.google.com/vpc-service-controls/docs/ingress-egress-rules) for publisher projects, exchange projects, and subscriber projects. For more information, see [Configure VPC Service Controls rules for BigQuery sharing](https://docs.cloud.google.com/bigquery/docs/analytics-hub-vpc-sc-rules).
- Data 360 data is shared as views. As a subscriber, you can't access the underlying tables that the views reference.

## What's next

- Learn how to [view and subscribe to listings and data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-view-subscribe-listings).
- Learn how to [grant BigQuery sharing roles](https://docs.cloud.google.com/bigquery/docs/analytics-hub-grant-roles).
- Learn how to [manage data exchanges](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-exchanges) and [manage listings](https://docs.cloud.google.com/bigquery/docs/analytics-hub-manage-listings).