1. Snowflake Iceberg Tables Now Generally Available

Snowflake Iceberg Tables have moved to general availability, offering full storage interoperability with the Apache Iceberg open table format. This feature facilitates easier governance and collaboration on Iceberg data stored externally, enhancing the flexibility of data lakehouses, data lakes, and data meshes. Over 300 customers have already adopted Iceberg in its public preview, highlighting its potential to broaden Snowflake’s data footprint.

2. Advancements in Snowflake Cortex AI

Snowflake introduced several enhancements to Cortex AI, including:

• • Cortex Analyst: Built with Meta’s Llama 3 and Mistral Large models, this tool allows businesses to build applications securely on top of Snowflake’s analytical data.
• • Cortex Search: Leveraging Neeva’s retrieval and ranking technology, it facilitates the development of apps against documents and text-based datasets.
• • Cortex Guard: Aiming to ensure model safety, it filters and flags harmful content, including violence and hate speech.
• • Document AI: This feature, powered by Snowflake Arctic-TILT multimodal LLM, will soon allow users to extract data from documents such as invoices and contracts.

3. Introduction of Polaris Catalog

The Polaris Catalog is a vendor-neutral, open catalog implementation for Apache Iceberg, providing cross-engine interoperability and greater flexibility. It will become open-sourced within 90 days, supporting a variety of engines, including Apache Flink, Apache Spark, and Trino.

4. Private Preview of Snowflake Horizon Updates

Snowflake launched a private preview of an internal model marketplace within Snowflake Horizon. This marketplace enables users to publish and curate models, applications, and data products for internal use ensuring controlled access and preventing unintended external sharing. Other upcoming features include AI model sharing and AI-powered object descriptions.

5. AI & ML Improvements

• • Snowflake AI & ML Studio: A no-code interactive interface for AI development, now in private preview.
• • Cortex Fine-Tuning: In public preview, allowing customization of pre-trained models for specialized tasks.
• • ML Lineage: In private preview, offering traceability across ML life cycles.
• • Feature Store: Now in public preview, for creating, managing, and serving ML features.

6. Snowflake Native Apps with Snowpark Container Services — Preview

Snowflake introduced the integration of the Native App Framework with Snowpark Container Services on AWS. This integration provides developers with configurable GPU and CPU instances for various applications, from computer vision to geospatial data analysis. Over 160 Snowflake Native Apps are now available in the marketplace.

7. Developer Tool Enhancements

Several updates aimed at developers include:

• • Snowflake Notebooks: Snowflake Notebooks is now in preview, offering an interactive, cell-based programming environment for Python and SQL within Snowsight. It enables exploratory data analysis, machine learning model development, and other data science tasks all in one place.
• • Snowpark pandas API: Allows the use of pandas syntax for AI and pipeline development within Snowflake. The Snowpark pandas API is now in preview, allowing you to run pandas code directly on Snowflake data. This API offers a pandas-native experience with Snowflake’s scalability and security, handling larger datasets without rewriting pandas pipelines.
• • Database Change Management: A public preview feature for DevOps, including Git integration.
• • Python API and CLI: Soon to be generally available, facilitating CI/CD practices.

8. Expanded Cloud Footprint and Governance

Snowflake announced a new data boundary for the EU, ensuring regional data residency and compliance. Additionally, a Department of Defense (DoD) environment meeting IL4 security controls will be available, highlighting Snowflake’s commitment to robust data governance and security.

9. Snowflake Trail

The new Trail set of observability capabilities was unveiled, providing developers with tools to monitor, troubleshoot, and optimize workflows. Trail integrates with platforms like Grafana, Metaplane, and Slack, adhering to OpenTelemetry standards.

10. Snowflake Cortex Fine-Tuning — Preview

Cortex Fine-Tuning, now in preview, lets users adapt pre-trained models for specialized tasks. This managed service fine-tunes popular large language models using your data within Snowflake, enhancing model performance for specific use cases.

The preview of Snowpark Native Apps with Snowpark Container Services enables running containerized services within Snowflake Native Apps. This feature supports provider IP protection, security, data sharing, monetization, and integration with compute resources.

11. Snowpark Python Local Testing Framework — General Availability

The Snowpark Python local testing framework is now generally available. This emulator allows you to test Python code locally with Snowpark Python DataFrames, facilitating development and CI pipeline integration without needing a Snowflake account connection.

12. Universal Search and Snowsight Updates

Universal Search, now generally available, allows users to search for content across Snowflake storage, external Iceberg storage, and third-party providers. Snowsight also received a dark mode feature, enhancing user experience in low-light conditions.

13. New Geospatial Functions in Preview

Four new functions for GEOGRAPHY objects are now available in preview:

• • H3_TRY_COVERAGE: A special version of H3_COVERAGE that returns NULL if an error occurs when attempting to return an array of IDs (INTEGER values) identifying the minimal set of H3 cells that completely cover a shape.
• • H3_TRY_COVERAGE_STRINGS: Similar to H3_TRY_COVERAGE but returns hexadecimal IDs (VARCHAR values).
• • H3_TRY_POLYGON_TO_CELLS: Returns an array of INTEGER values of the IDs of H3 cells with centroids contained by a Polygon, returning NULL if an error occurs.
• • H3_TRY_POLYGON_TO_CELLS_STRINGS: Similar to H3_TRY_POLYGON_TO_CELLS but returns VARCHAR values.

With innovations in AI, data governance, and developer tools, Snowflake continues to drive forward the capabilities of its platform, ensuring customers can leverage data more effectively and securely. The future looks promising as Snowflake expands its offerings and strengthens its ecosystem, providing powerful solutions.