Snowflake Release Notes
153 release notes curated from 1 source by the Releasebot Team. Last updated: Jun 4, 2026
- Jun 2, 2026
- Date parsed from source:Jun 2, 2026
- First seen by Releasebot:Jun 4, 2026
Private connectivity for catalog-vended credentials (General availability)
Snowflake now supports outbound private connectivity for Apache Iceberg tables using catalog-vended credentials.
When you use catalog-vended credentials for Apache Iceberg™ tables, you can now configure outbound private connectivity so Snowflake accesses your cloud storage through a private endpoint instead of the public internet. You can enable private storage access by setting
USE_PRIVATELINK_ENDPOINT = TRUEin the
DEFAULT_STORAGE_CONFIGparameter of your catalog integration.
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Original source - Jun 1, 2026
- Date parsed from source:Jun 1, 2026
- First seen by Releasebot:Jun 1, 2026
Snowflake storage for Apache Iceberg™ tables (General availability)
Snowflake releases generally available storage for Apache Iceberg tables, managing table files without external cloud storage setup.
With this release, Snowflake storage for Apache Iceberg™ tables is now generally available. This option lets Snowflake store and manage the Iceberg table files for you, so you don't need to set up access to external cloud storage.
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- Jun 1, 2026
- Date parsed from source:Jun 1, 2026
- First seen by Releasebot:Jun 1, 2026
Optimized refresh for failover groups (Public Preview)
Snowflake adds optimized refresh public preview for failover groups to make account replication more efficient and predictable.
Optimized refresh is a new refresh mode for failover groups, now available in public preview. It makes account replication refreshes more efficient and predictable, and is especially valuable for customers who replicate a very large number of objects. You opt in per failover group by setting
OPTIMIZED_REFRESH = TRUEon the primary failover group. The mode works with the same failover group SQL surface you already use, and replication, failover, and failback semantics are unchanged.
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Original source - May 28, 2026
- Date parsed from source:May 28, 2026
- First seen by Releasebot:Jun 1, 2026
Planned price reduction for Cortex AI_TRANSCRIBE
Snowflake cuts Cortex AI_TRANSCRIBE pricing by up to 60% for more cost-effective audio and video transcription in Snowflake.
Effective June 1, Snowflake is reducing pricing for Cortex AI_TRANSCRIBE by up to 60%, making it more cost-effective to transcribe and analyze audio and video content directly in Snowflake.
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Original source - May 28, 2026
- Date parsed from source:May 28, 2026
- First seen by Releasebot:May 29, 2026
Dynamic tables immutability constraints renamed to frozen regions
Snowflake renames dynamic table immutability to frozen region and IMMUTABLE WHERE to FROZEN WHERE.
The dynamic tables feature formerly known as the immutability constraint is now called the frozen region of a dynamic table. As part of this rename, the IMMUTABLE WHERE clause is also renamed to FROZEN WHERE.
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Read more - May 28, 2026
- Date parsed from source:May 28, 2026
- First seen by Releasebot:May 28, 2026
Gemini 3.5 Flash available in Cortex AI Functions for multimodal video and audio analysis
Snowflake Cortex AI_COMPLETE now supports Gemini 3.5 Flash for multimodal video and audio analysis in Snowflake.
Snowflake Cortex AI_COMPLETE now supports Gemini 3.5 Flash for multimodal video and audio analysis, enabling organizations to extract brand, sentiment, behavioral, and content insights from rich media directly in Snowflake. With frontier multimodal intelligence and Flash-level speed, teams can analyze video and audio content for marketing, content intelligence, compliance, and media analytics workflows without moving data outside of Snowflake.
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Read more - May 28, 2026
- Date parsed from source:May 28, 2026
- First seen by Releasebot:May 28, 2026
Sensitive Data Access report (Public Preview)
Snowflake adds Sensitive Data Access reports to show which users accessed sensitive data during a lookback period.
You can now generate a Sensitive Data Access report to view which users accessed sensitive data in your account during a specified lookback period. The report creates a view that lists user-table-role combinations identified in query and access history for classified tables.
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Original source - May 27, 2026
- Date parsed from source:May 27, 2026
- First seen by Releasebot:May 28, 2026
Data protection policies in Snowsight (Public Preview)
Snowflake adds preview data protection policy management in Snowsight for dashboards, policy lists and protected objects.
With this preview release, you can use the Governance & security » Data protection policies area in Snowsight to create data protection policies from the Dashboard, list and manage policies on the Policies tab, and view protected objects on the Objects with policies tab.
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Original source - May 26, 2026
- Date parsed from source:May 26, 2026
- First seen by Releasebot:May 27, 2026
- Modified by Releasebot:May 28, 2026
Snowflake Data Clean Rooms updates
Snowflake adds new Data Clean Rooms API capabilities in version 15.6, including a public preview DCR Agent for conversational collaboration and approved analyses, plus expanded Cortex Code Skills for collaboration management and template request workflows.
Clean Rooms API Version: 15.6
The following new features and enhancements are now available in Snowflake Data Clean Rooms:
- DCR Agent (public preview): You can now use a conversational Snowflake Intelligence interface to join collaborations and run approved analyses including audience overlap and activation via standard_audience_overlap_v0 and standard_audience_overlap_activation_v0 templates.
- Learn more.
- Additional Cortex Code Skills: Users can now use cortex code with data clean room skills that support dropping/leaving a collaboration, linking/unlinking data offerings and requesting new templates to be added with approval flows.
- May 26, 2026
- Date parsed from source:May 26, 2026
- First seen by Releasebot:May 27, 2026
Adaptive refresh mode for dynamic tables (Public Preview)
Snowflake adds ADAPTIVE refresh mode support for dynamic tables.
Dynamic tables now support a new refresh mode: REFRESH_MODE = ADAPTIVE.
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Original source - May 26, 2026
- Date parsed from source:May 26, 2026
- First seen by Releasebot:May 27, 2026
Custom incremental dynamic tables (Public Preview)
Snowflake adds CUSTOM_INCREMENTAL refresh mode for dynamic tables, enabling MERGE or INSERT logic with managed scheduling and retries.
When standard refresh modes don't support your transformation pattern, CUSTOM_INCREMENTAL refresh mode lets you write MERGE or INSERT logic that Snowflake executes on each refresh. You define exactly how changes reach the dynamic table while Snowflake handles scheduling, retries, and transactional guarantees. This mode supports patterns such as stream-static joins, soft-deletes, stateful aggregation, and direct migration from streams and tasks.
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Original source - May 26, 2026
- Date parsed from source:May 26, 2026
- First seen by Releasebot:May 26, 2026
Apache Iceberg™ tables: Write support by using an external query engine (General availability)
Snowflake adds general availability for external query engine support on Snowflake-managed Apache Iceberg tables via Horizon Catalog.
With this release, write support for Snowflake-managed Apache Iceberg™ tables by using an external query engine through Snowflake Horizon Catalog is now generally available. You can read and write to Snowflake-managed Iceberg v2 and v3 tables from any external query engine that supports the open Iceberg REST protocol, such as Apache Spark™, by using a single Horizon Catalog endpoint and your existing Snowflake users, roles, policies, and authentication.
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Original source - May 22, 2026
- Date parsed from source:May 22, 2026
- First seen by Releasebot:May 23, 2026
AI_EXTRACT extraction scores (General availability)
Snowflake releases generally available extraction scores for the Cortex AI_EXTRACT function, adding confidence scoring for extracted values and support for entities, lists, tables, and fine-tuned arctic-extract models.
Extraction scores for the Snowflake Cortex AI_EXTRACT function are now generally available. Key capabilities include:
- Confidence scores for extracted values: Pass scores => TRUE in an AI_EXTRACT call to get back a scoring object alongside the standard response object, with a score between 0 and 1 indicating the model's certainty about each extracted value.
- Support for entities, lists, and tables: Per-field scores are returned for entity extraction, and aggregate scores are returned for list and table extraction.
- Support for fine-tuned arctic-extract models: Extraction scores work with fine-tuned arctic-extract models in addition to the default model.
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Original source - May 21, 2026
- Date parsed from source:May 21, 2026
- First seen by Releasebot:May 22, 2026
Dynamic tables documentation rewritten
Snowflake expands dynamic tables documentation with 30 new and updated pages for building, optimizing, monitoring, and troubleshooting pipelines.
The dynamic tables documentation now includes 30 new and updated pages covering the full lifecycle of building, optimizing, monitoring, and troubleshooting dynamic table pipelines.
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Original source - May 21, 2026
- Date parsed from source:May 21, 2026
- First seen by Releasebot:May 22, 2026
Storage lifecycle policies for dynamic tables (General availability)
Snowflake adds generally available storage lifecycle policies for dynamic tables to delete or archive matching rows on an independent schedule.
Attaching a storage lifecycle policy to a dynamic table is now generally available. You can attach a storage lifecycle policy directly to a dynamic table to delete or archive rows that match a predicate, on a schedule that runs independently of dynamic table refresh.
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Curated by the Releasebot team
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