Snowflake Pioneers New Open Framework

Snowflake Pioneers New Open Framework for Interoperable Enterprise Data and AI

Snowflake advances interoperability without compromise across every layer of modern data architecture, enabling teams and AI agents to work from a single, governed, and logical data copy

Snowflake announced new capabilities that redefine interoperability for the AI era, enabling organizations to seamlessly access, govern, share, and act on data across systems without compromise.

For the first time, enterprises can work on a single, live, governed copy of their data wherever it resides across Snowflake, external lakes, and open systems, without moving or duplicating it. Powered by Snowflake Horizon Catalog, organizations can now transform siloed data into a connected, AI-ready foundation where users and AI agents securely discover, govern, and access their full business context.

Snowflake is advancing open interoperability with support for Apache Iceberg v35, 1 and Snowflake Storage for Apache Iceberg Tables5, 1, enabling teams to seamlessly work across data inside and outside of Snowflake, while minimizing data movement. In addition, Horizon Catalog powered by Apache Polaris6 enables bi-directional read and write access1 using external engines to Iceberg data managed by Snowflake. Snowflake also extends consistent governance across open ecosystems with external engine access management4 and support for Iceberg REST Scan Plan API4, ensuring fine grained protections apply across compatible engines. Together, these capabilities give organizations a unified, governed foundation for data and AI, unlocking interoperability without compromise.

“Most organizations still rely on moving and duplicating data just to make it usable, and that approach simply cannot keep up with the pace of AI. As innovation accelerates, data fragmentation becomes the constraint,” said Christian Kleinerman, EVP of Product, Snowflake. “We are fully committed to interoperability and openness. With Snowflake’s capabilities, we are ushering in a new model for enterprise data, where customers can work directly on live, governed data wherever it resides through a single, connected governance plane. By eliminating duplication and defining shared business meaning through semantic views, we’re establishing a consistent, trusted foundation for both teams and AI agents.”

"At Affirm, delivering transparent and responsible financial products starts with having a clear, consistent view of our data,” said Vivek Anandpara, VP of Engineering, Affirm. “Snowflake enables us to work across systems without duplicating data, while applying governance consistently across our environment. This gives our teams a trusted foundation to move faster, improve decisioning, and scale AI with confidence. Our migration of thousands of tables and critical financial workloads to Polaris using Snowflake's interoperable and governed data foundation proved that out — Snowflake partnered closely with us to deliver zero-downtime correctness at scale."

Open, Multi-Engine Access with the Interoperable Lakehouse for the AI Era

As enterprises scale their AI initiatives, traditional architectures create complexity and drive up costs. Data is often fragmented across platforms and operational systems, forcing organizations to spend valuable time copying, stitching together, and reconciling data before it can be used. This operational overhead delays AI initiatives and creates inconsistent data foundations that make it harder for AI systems to deliver reliable outcomes.

Snowflake removes these barriers by enabling teams to work directly on live data wherever it resides, without movement or duplication. By combining open connectivity, intelligent querying, and support for open standards, Snowflake creates a single data foundation that allows organizations to access, understand, share, and act on all their data.

New interoperability features enable organizations to:

Build on open standards with Apache Iceberg: With Apache Iceberg v3 support now generally available, Snowflake delivers broad support for the latest open table format innovations, including more data types, cross-system change tracking, and high performance on semi-structured data. This helps organizations eliminate fragmented data architectures and reduce costly data movement across platforms and engines. Coupled with Snowflake Storage for Apache Iceberg Tables, organizations can now reduce data movement and operational overhead with a fully managed experience for open data at scale.
Access and activate key enterprise data without movement: Snowflake, powered by native Apache Iceberg support and Horizon Context, enables organizations to seamlessly access and act on data across Snowflake and external data lakes without moving or duplicating it. Major platforms like SAP1, Salesforce2, and Workday4, along with new partnerships with AVEVA and IBM, can be accessed without replication using Zero-Copy Integrations, while preserving the business context, policies, and logic that power critical operations and decisions. A dedicated Skill for SAP1 in Snowflake CoCo, Snowflake’s AI coding agent, streamlines how developers connect to, explore, and manage SAP data within Snowflake.
Securely talk to all data: Organizations can now empower users to self-serve trusted business insights across their entire data estate using natural language, without requiring manual integration or deep technical expertise. CoCo enables users to ask questions across Snowflake, external data lakes, and now, external relational database systems4, while Horizon Context automatically identifies the right data and applies trusted business context. This enables faster, more reliable decision making on a fully governed data platform.
Make shared data instantly agentic: Auto-gen Agents for Data Shares and Listings3 let providers turn any shared data listing or secure data share into a conversational AI agent, ready to use in CoCo, Snowflake CoWork, or Snowsight. With Cortex Agent Sharing3, agents can be deployed across Snowflake accounts to internal teams, partners, or in Snowflake Marketplace. Consumers can ask questions in natural language, combine shared data with their own first-party data for richer insights, and get enterprise governance out of the box.

“At Indeed, we empower our teams to securely access and act on trusted data across systems, which actively drives our global scale and creates better hiring experiences,” said Trey Henninger, VP Data and Analytics, Indeed. “Snowflake’s interoperable approach streamlines our architecture, slashing unnecessary data movement while maintaining strict governance and flexibility across platforms. This builds a powerhouse foundation for innovation and accelerates how quickly we deploy new AI-powered capabilities.”

“As we expand our data and AI initiatives, it’s critical that we can work across systems without adding complexity,” said Yoshio Umezawa, Vice President General Manager of Service Innovation Department R&D Innovation Division, NTT DOCOMO, INC. “Snowflake allows us to access and govern data wherever it resides, while maintaining a consistent, trusted foundation. This helps our teams move faster, reduce operational overhead, and deliver more intelligent services to our customers.”

“At Samsung Ads, delivering relevant and measurable advertising experiences depends on having seamless access to trusted data across a complex ecosystem,” said Hervé Marcellini, Vice President of Engineering, Samsung Ads. “Snowflake enables us to work across systems without duplicating data, while maintaining consistent governance throughout our environment. This allows our teams to move faster, improve targeting and measurement, and scale AI-driven innovation with confidence.”

Centralized Governance and Control Across Systems As data becomes increasingly distributed and AI systems operate with greater autonomy, organizations face growing challenges in consistently governing, securing, and auditing data across every system where it is accessed, shared, and used. Snowflake addresses this challenge with Horizon Catalog, powered by Apache Polaris6, providing a single, connected foundation for governance across enterprise data inside and outside of Snowflake. By centralizing how data is discovered, secured, and monitored, Horizon Catalog ensures policies are applied consistently, access is controlled across environments, and organizations can operate with confidence as they scale AI on a single, governed, and live data copy.

New capabilities in Horizon Catalog enable organizations to:

Securely access Snowflake managed Iceberg tables through open security controls: Snowflake managed Iceberg tables deliver optimized performance on Snowflake, while providing flexible controls to improve performance across other engines. Horizon Catalog, powered by Apache Polaris6, enables secure, governed, bi-directional read and write access to Snowflake managed Iceberg tables from external engines through open, standards-based access controls defined by the Iceberg community. This ensures organizations can connect multi-platform data architectures under one governance layer, without proprietary lock in or operational friction.
Achieve universal access controls across engines for any Iceberg Table: Building on Catalog Linked Databases, which automatically make external Iceberg Tables discoverable and accessible in Snowflake, organizations can now use external engine access management4 to enable secure engine access to external tables for read and write operations, making Horizon Catalog the universal catalog for enterprise data. The result is a single, metadata driven control plane that unifies governance, security, and policy enforcement across multi-catalog environments.
Extend consistent governance across environments: Support for Data Protection Policies1, such as column masking and row access enforcement using the open source Iceberg REST Scan Plan API, ensures fine-grained access control across Iceberg-compatible engines. Combined with Sensitive Data Classification1 and Data Quality controls1, Snowflake customers can now define policies and centrally manage governance in Horizon Catalog. This universal governance layer for all Iceberg tables enables organizations to seamlessly discover, secure, and govern data across environments
Share data across any engine or platform: Open Data Sharing enables organizations to securely share data and AI assets with customers, partners, and internal teams on any engine, without copies. Recipients access directly from the platforms, tools, and engines of their choice with consistent governance and lineage intact. With no data movement, duplicate compute, or vendor lock-in, customers benefit from simpler collaboration, lower infrastructure costs, and greater flexibility. Providers share once, and consumers access from anywhere.
Gain full visibility and auditability across systems: Connected Audit Access in Horizon4 and new observability for externally managed Iceberg Tables4 give organizations a centralized view into data access and pipeline health across Snowflake and external environments, helping teams proactively monitor activity, troubleshoot issues faster, and operate with greater confidence.

Source: Snowflake media announcement

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