April 29, 2024 — Dynamic Tables — General Availability

With this release, we are pleased to announce the general availability of dynamic tables, which are a new table type for continuous processing pipelines. Whether you’re processing batch data daily or real time data in minutes, dynamic tables allow you to create data pipelines that are easy to build, operate, and evolve.

With general availability, the following new enhancements are added:

  • Sharing and collaboration: Dynamic tables can now be shared across regions and clouds using Snowflake’s sharing and collaboration features. This makes it easy to share clean, enriched, and transformed data products with consumers in your organization, partner organizations, or the broader data cloud community, ensuring they stay updated according to your specified cadence.

  • Disaster recovery and replication: Dynamic tables now support high availability through Snowflake’s replication infrastructure. You can build your production pipelines with peace of mind knowing that you’re supported with Snowflake’s disaster recovery solutions.

  • Observability: New functionality added for better observability via Snowsight and programmatic interfaces. In Snowsight, there are new account-level views, visibility into warehouse consumption, improved graph and refresh history, and the ability to suspend and resume refreshes. Observability functions now include new account usage views, extended retention of information schema functions and added support for consistent metadata across Snowflake observability interfaces.

  • Data Cloud integrations: Added support for clustering, transient dynamic tables, and governance policies (on sources of dynamic tables and dynamic tables themselves), allowing you to benefit from the best features of the Snowflake Data Cloud.

  • Scalability: You can now create four times more dynamic tables in your account, and ten times more dynamic table sources feeding into another dynamic table. There are no longer any limits on the depth of a directed acyclic graph (DAG) that you can create.

  • Query evolution support: Dynamic tables now automatically evolve to absorb new columns from base tables without needing to rebuild the dynamic table when new columns are added, as long as the changes do not affect the schema of the dynamic table.

  • New documentation: We’ve added new articles to our documentation covering development best practices, performance optimization guides, troubleshooting pipeline issues, and other improvements.

Additionally, Snowflake has made numerous under-the-hood refinements to enhance refresh performance, system stability and scalability.

For more information, see Dynamic tables.