.jpg)
Snowflake has announced key platform advancements designed to unify and govern enterprise data, making it inherently ready for artificial intelligence workloads. Central to this is the upcoming general availability of Snowflake Postgres, bringing the popular transactional database natively into the AI Data Cloud to eliminate silos and complex data pipelines between operational and analytical systems.
Snowflake announces the upcoming general availability of Snowflake Postgres, integrating the database natively into its platform.
This aims to unify transactional, analytical, and AI workloads, eliminating complex data pipelines.
Enhanced Snowflake Horizon Catalog governance now extends to data queried by external engines like Apache Spark.
New Open Format Data Sharing enables secure sharing of data in Apache Iceberg and Delta Lake formats.
Snowflake Backups become generally available to strengthen data resilience against ransomware and disruptions.
Early adopters include BlueCloud, Sigma Computing, Merck, and Motorq.
A primary innovation is Snowflake Postgres, which allows the widely-used PostgreSQL database to run natively within Snowflake's platform. This is powered by pg_lake, a set of extensions that enable Postgres to work directly with data in the open Apache Iceberg format. The goal is to allow enterprises to run mission-critical applications, perform real-time analytics, and build AI agents all on the same platform using the most current operational data, without the latency, cost, and complexity of building and maintaining separate data pipelines between systems.
To ensure AI systems are built on trusted data, Snowflake is enhancing Snowflake Horizon Catalog, its unified governance layer. A key new capability allows governance policies—such as security tags and masking—to be enforced even when Snowflake-managed data in Iceberg tables is queried by external engines like Apache Spark. This provides enterprises with the freedom to use the best tools for the job without breaking governance or creating new data silos, a feature being used by customers like Merck and Motorq.
The announcements further focus on secure data collaboration and protection. Open Format Data Sharing extends Snowflake's zero-copy data sharing model to open table formats like Apache Iceberg and Delta Lake, enabling seamless, governed data exchange. A new integration with Microsoft OneLake facilitates bidirectional access for Iceberg data managed in either Snowflake or Microsoft Fabric. To combat rising cyber threats, Snowflake Backups provide immutable, point-in-time recovery for business-critical data, helping organizations meet regulatory requirements and recover from incidents like ransomware attacks.
Snowflake's latest innovations represent a strategic push to solve the foundational data challenges that impede enterprise AI at scale. By natively integrating a leading transactional database and deepening open data interoperability with rigorous governance, Snowflake is positioning its platform as the unified "source of truth" where data is not just stored but is actively prepared, governed, and protected for production AI. This moves beyond simply running AI models to creating an environment where data is AI-ready by design, reducing the operational burden and risk associated with deploying intelligent systems.
About Snowflake
Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 12,000 customers around the globe, including hundreds of the world’s largest companies, use Snowflake’s AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone.
TechIntelPro empowers B2B technology decision-makers with the latest industry trends, deep insights, leadership perspectives and actionable intelligence to drive both organizational and professional milestones—and thrive on the tech pulse.