Snowflake (NYSE: SNOW) has quickly established itself as a key player in the data industry, transforming how cloud developers, data managers, and data scientists work with data. Its innovative architecture separates storage from compute resources, enabling organizations to scale each independently for optimal cost efficiency and performance. Designed for security and scalability, Snowflake empowers cloud developers to build data-driven applications without the burden of managing underlying infrastructure. Data managers leverage its data-sharing capabilities to promote secure, real-time collaboration across departments and partners. Meanwhile, data scientists benefit from Snowflake’s ability to handle large, diverse datasets and its seamless integration with machine learning tools, making it easier to prepare data, build models, and generate actionable insights. Keep an eye on this page for the latest news and developments related to Snowflake.

Snowflake Announces Acquisition of Select Star to Enhance Horizon Catalog

November 21, 2025: Snowflake announced its plan to acquire Select Star, a startup specializing in metadata management and data discovery, to strengthen its Horizon Catalog. This suite within Snowflake’s Data Cloud aims to provide a unified platform for data discovery, management, and governance. The acquisition will enhance Snowflake’s ability to deliver comprehensive metadata insights and streamline data governance processes for enterprise customers.

Horizon Catalog is a core component of Snowflake’s efforts to simplify data management and improve collaboration across organizations. The integration of Select Star’s expertise is expected to provide users with richer metadata, better data discovery, and more efficient governance capabilities.

Competitive Moves in Enterprise AI: Snowflake and Databricks Face Off

November 13, 2025: In an ongoing rivalry, Snowflake and Databricks are competing over enterprise AI capabilities, specifically in SQL-based document parsing. Databricks recently introduced SQL-based AI parsing within its Agent Bricks framework, just days after Snowflake unveiled a similar feature within its Intelligence platform. This development highlights the growing importance of AI-driven automation for enterprise data workloads.

This competition underscores the race for dominance in AI-powered data processing, with both companies expanding their offerings to provide more advanced, integrated solutions for their customers.

Stay tuned for further updates as both platforms continue to innovate in this space.

Snowflake Expands Migration Capabilities with Acquisition of Datometry

November 11, 2025: Snowflake announced its acquisition of Datometry, a San Francisco-based startup focused on automated database migration tools, for an undisclosed amount. This move aims to enhance Snowflake’s SnowConvert AI, a tool designed to streamline migration processes for enterprises transitioning to Snowflake’s platform.

The acquisition will help reduce migration complexity and improve the speed and accuracy of moving large datasets and workloads into Snowflake, making it easier for organizations to adopt and scale their data initiatives.

New Features: Running Apache Spark Analytics Directly on Snowflake

July 29, 2025: Snowflake announced Snowpark Connect for Apache Spark, allowing users to run Spark analytics workloads directly within Snowflake’s infrastructure. This new feature eliminates the need for external Spark instances and reduces data transfer delays, improving efficiency and performance for data teams.

This integration simplifies the analytics process by consolidating workloads within Snowflake’s platform, enabling faster insights and easier management of big data environments.

Performance and Cost Optimization with Snowflake’s Adaptive Technology

June 4, 2025: Snowflake introduced Adaptive Warehouses, a new feature built on its Adaptive Compute technology, designed to optimize performance and reduce costs. This innovation helps enterprises manage compute resources more effectively by automatically adjusting resource sizing and sharing, balancing performance needs with cost efficiency.

With Adaptive Warehouses, Snowflake aims to address traditional challenges related to resource management and legacy data workflows, empowering organizations to run analytics more smoothly and economically.

Inspired by

• https://www.infoworld.com/article/4002605/snowflake-latest-news-and-insights.html

Sources

• yahoo.com