BigQuery sharing review
A BigQuery-native exchange for governed data sharing, discovery, and direct querying.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
BigQuery sharing, formerly Analytics Hub, is a Google Cloud data exchange platform for publishing, discovering, subscribing to, and querying shared datasets and Pub/Sub topics. Providers can organize resources into public or private exchanges, create listings, set IAM permissions, manage subscriptions, and monitor usage. Subscribers can create linked datasets or Pub/Sub subscriptions in their own projects and query shared data without replicating the underlying resources. It is designed for organizations sharing data internally, with partners, or through public and commercial exchanges.
The published commercial model is contact sales. According to the vendor’s pricing notes, managing exchanges or listings carries no additional charge, while subscribers and publishers may incur underlying BigQuery, Pub/Sub, or Google Cloud Marketplace-related charges. BigQuery sharing connects directly with BigQuery, Pub/Sub, and Google Cloud Marketplace, giving providers a path from publishing to subscription management and commercialization. That platform alignment makes it a practical fit for teams whose data products already depend on Google Cloud services.
Its standout capability is governed access to shared data without copying the underlying resources. Providers can publish BigQuery datasets and Pub/Sub topics as listings, control access at exchange and listing levels through IAM, and track jobs, subscribers, rows, and bytes processed. Subscribers can query shared BigQuery tables and views directly, while read-only linked datasets help preserve the provider’s source environment. Choose BigQuery sharing when direct querying, private exchanges, and Google Cloud controls matter more than a standalone marketplace stack. Teams seeking a fixed, self-serve pricing structure or a platform centered outside BigQuery, Pub/Sub, and Google Cloud Marketplace should consider alternatives.
BigQuery sharing pros and cons
- Where it wins
- Shares datasets and Pub/Sub topics through public or private exchanges
- Enables read-only linked datasets without replicating underlying data
- Combines IAM controls, subscriptions, usage tracking, and Marketplace sales
- Where it doesn't
- Pricing follows a contact-sales model rather than a published fixed plan
- Subscribers and publishers may incur underlying service-related charges
- Best suited to organizations already operating in the Google Cloud ecosystem
BigQuery sharing fact sheet, pricing and score →
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