What Is BigQuery sharing?
BigQuery sharing, formerly Analytics Hub, is Google Cloud’s data exchange platform. It lets you securely share, discover, and access data across organizational boundaries without replicating data.
The model follows a publisher-subscriber pattern: publishers create shared resources and publish listings, subscribers discover and subscribe to them. Subscribing creates a read-only linked dataset in the subscriber’s project that points to the original data, so queries run directly against the underlying tables and views.
Core Capabilities
- Data exchanges as containers for listings, either private with restricted access or public for all Google Cloud users
- Listings with descriptions, sample queries, and contact information
- Linked datasets as read-only pointers without data replication
- A broad range of shareable resources: tables, views and materialized views, authorized views and datasets, BigQuery ML models, external tables, routines, and table snapshots
- Pub/Sub topics shareable in addition to datasets
- Column-level and row-level security on shared datasets
- Egress controls: publishers can restrict exports, copies, and snapshot operations
Typical Use Cases
Enterprise data exchange: Business units provide data products without replicating copies into every consuming project.
Sharing with partners: Private data exchanges let you share selected datasets with specific external partners.
Internal data marketplace: Listings with descriptions and sample queries make existing datasets discoverable.
Streaming data: Beyond datasets, Pub/Sub topics can also be offered as listings.
Benefits
- No copying and no synchronization of datasets
- No additional cost for managing data exchanges and listings
- Fine-grained access control at column and row level
- Publisher control over exports, copies, and snapshots
- Discoverability through listings with descriptions and sample queries
Working with innFactory
As a certified Google Cloud Partner, innFactory supports you with BigQuery sharing:
- Data sharing design: structuring data exchanges and listings along your organizational and partner landscape
- Access control: implementing column-level and row-level security plus egress controls
- Data products: shaping internal datasets into discoverable, documented data products
- Operations: monitoring subscriptions and the cost of the underlying resources
Get in touch for a consultation on BigQuery sharing and data sharing architectures.
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is 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.
What are data exchanges and listings?
A data exchange is a container that organizes listings and enables publishers to share resources with subscribers. A listing is a reference to a shared resource published within a data exchange and can carry descriptions, sample queries, and contact information. Both can be private or public.
What is a linked dataset?
Subscribing to a listing creates a read-only BigQuery dataset in the subscriber's project. It acts as a pointer to the shared data without replication, so queries run directly against the underlying tables and views.
Which resources can be shared?
Publishers can share BigQuery datasets containing tables, views and materialized views, authorized views and datasets, BigQuery ML models, external tables, routines such as UDFs, table functions and stored procedures, and table snapshots. Pub/Sub topics can be shared as well.
What does BigQuery sharing cost?
Per the documentation there is no additional cost for managing data exchanges or listings. Pricing applies to the underlying resources - storage and queries for datasets, and publish/subscribe throughput for Pub/Sub topics.
How do I control what subscribers can do?
Shared datasets support column-level security and row-level security. In addition, publishers can restrict exports, copies, and snapshot operations.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of Google Cloud (official documentation). This page does not represent an offer by Google Cloud.
