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BigQuery Data Clean Rooms
Mountain View, California, United States
What it is
BigQuery Data Clean Rooms is a cloud service for multiple parties to share and analyze data while keeping the underlying data in place. It connects to BigQuery sharing, formerly called Analytics Hub, and supports campaign planning, measurement and attribution, activation, and applications in areas such as retail, financial services, healthcare, and supply chains. A room can include BigQuery tables, views, or table-valued functions. Owners manage rooms, contributors publish data, and subscribers run queries. Contributors can set analysis rules, including aggregation thresholds, and provide query templates with approved queries without exposing the underlying tables or views. The service blocks subscribers from copying or exporting raw data, and contributors can configure controls for query results. However, Google warns that analysis rules might not stop sophisticated queries from extracting unauthorized data. Rooms support up to 100 shared resources and are available only in BigQuery sharing regions; cross-region listings are not supported. Setup requires enabling the Analytics Hub API and assigning required IAM roles. Contributors pay for storage, while subscribers pay for compute when they query.
For and against
For
- Aggregation rules can limit subscribers to summarized analysis.
- Query templates provide predefined queries without exposing underlying tables.
- Raw data copying and exporting by subscribers is blocked.
- Owners can manage rooms in the console or create them through the API.
Against
- Analysis rules may not stop sophisticated data-extraction queries.
- Rooms are limited to 100 shared resources.
- Listings across multiple regions are not supported.
- Setup requires API enablement and IAM role assignments.
The verdict
BigQuery Data Clean Rooms provides controls for sharing BigQuery resources and querying them without exporting raw data. Its region, resource-count, setup, and privacy limitations are important to consider when planning a collaboration.
Who it suits
It suits organizations that need to share and analyze BigQuery data with partners while restricting access to raw data. Contributors and subscribers should account for the separate storage and query-compute charges.
Plans and prices
Data contributor
Publishes data to a clean room
Read 20 Sep 2026 · docs.cloud.google.com
Data clean room subscriber
Subscribes to and queries clean-room data
Read 20 Sep 2026 · docs.cloud.google.com
On the record
- Access setup
- Using data clean rooms requires enabling the Analytics Hub API and assigning the required IAM roles, including Analytics Hub Admin for owners.docs.cloud.google.com · read 2 Oct 2026
- Analysis controls
- Contributors can configure analysis rules, including aggregation thresholds, to restrict how subscribers query shared data.docs.cloud.google.com · read 2 Oct 2026
- BigQuery sharing
- Data clean rooms integrate with the BigQuery sharing platform, formerly called Analytics Hub.docs.cloud.google.com · read 3 Oct 2026
- Egress controls
- Data egress controls automatically prevent subscribers from copying or exporting raw data, and contributors can add controls for query results.docs.cloud.google.com · read 3 Oct 2026
- Interfaces
- The documentation describes managing clean rooms in the Google Cloud console and creating them through the API.docs.cloud.google.com · read 2 Oct 2026
- Limitations
- Analysis rules can be set only on views, and Google cautions that rules might not prevent sophisticated queries from extracting unauthorized data.docs.cloud.google.com · read 3 Oct 2026
- Pricing
- Data contributors are charged only for data storage, and subscribers are charged only for compute when they run queries.docs.cloud.google.com · read 3 Oct 2026
- Pricing basis
- Contributors are charged for data storage, while subscribers are charged for compute when they run queries.docs.cloud.google.com · read 2 Oct 2026
- Privacy controls
- Contributors can configure analysis rules, including an aggregation threshold rule that allows subscribers to analyze data only through aggregation queries.docs.cloud.google.com · read 3 Oct 2026
- Privacy limitation
- Google cautions that analysis rules might not prevent sophisticated queries from extracting unauthorized data and recommends query templates for approved-query control.docs.cloud.google.com · read 2 Oct 2026
- Purpose
- BigQuery data clean rooms let multiple parties share, join, and analyze data without moving or revealing the underlying data.docs.cloud.google.com · read 3 Oct 2026
- Query templates
- Owners and publishers can share predefined queries through query templates without sharing the underlying tables or views.docs.cloud.google.com · read 3 Oct 2026
- Regional availability
- Data clean rooms are available only in BigQuery sharing regions, and listings for multiple regions are unsupported.docs.cloud.google.com · read 3 Oct 2026
- Resource limit
- A data clean room can contain at most 100 shared resources; Google directs users to contact [email protected] to request an increase.docs.cloud.google.com · read 3 Oct 2026
- Roles
- The product defines owner, contributor, and subscriber roles for managing rooms, publishing data, and querying shared data.docs.cloud.google.com · read 3 Oct 2026
- Shared resources
- A shared resource must be a BigQuery table, view, or table-valued function routine.docs.cloud.google.com · read 3 Oct 2026
- Use cases
- Google lists campaign planning, measurement and attribution, activation, retail, financial services, healthcare, and supply chain use cases.docs.cloud.google.com · read 3 Oct 2026
