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AI is exposing the cost of data fragmentation. Snowflake’s interoperable lakehouse built on Apache Iceberg™ and Polaris™ gives you interoperability without compromise. Read and write to any Iceberg table — from Snowflake or any engine — to eliminate data movement, reduce costs and fuel AI with governed, live data and no lock-in.
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Cut costs with a single governed data copy any engine can read and write: resilient, shareable and ready for any operation.
Persist policies across engines to simplify governance and reduce security risks, with no vendor lock-in.
Build portable business context in your data so AI can succeed anywhere.
UNIVERSAL GOVERNANCE
Build an open, metadata-driven governance and security model that connects all your data with fine-grained access controls — at the table, row and column level — that persist across engines without vendor lock-in. Powered by Horizon Catalog, based on Apache Polaris™.

Manage secure, multi-engine read and write access from any Iceberg REST-compatible engine with fine-grained policies that travel with the data.
Detect and classify sensitive data on any table to mitigate compliance and security risks. Built-in intelligence allows you to get the most value from AI, safely.
Apache Iceberg™ and Apache Polaris™ are governed by the community, not a single vendor. Your data stays portable, your architecture stays yours.
ONE DATA COPY
Read and write to any Iceberg table and query Delta and Parquet wherever it lives, with enterprise-grade price-performance and no data duplication.

Create Iceberg tables that any engine can read and write without managing buckets. Snowflake Storage for Apache Iceberg™ Tables delivers full interoperability, zero overhead.
Keep your interoperable lakehouse running when outages occur by writing three command lines to replicate across clouds and regions with automatic failover.
Federate from any Iceberg REST-compatible catalog with full read-write access to build a connected, governed view of your data estate with automatic discovery and refresh.
Users can read and write natively without adopting your stack, since you can easily share governed Iceberg and Delta tables across any engine, cloud and platform.
Extend Snowflake’s industry-leading price-performance to a broader set of Iceberg use cases with native support for the V3 specification.
Reduce TCO and accelerate performance of your existing Spark workloads.
Automate compaction, snapshot expiry and cleanup with intelligent table optimization — tuned for any engine you use, in your existing storage.
Feed any data source into your AI pipelines. Preserve metadata and semantics with superior economics for stream or batch ingestion.
BUSINESS LOGIC
Business logic is defined differently across every tool, team and AI agent, leading to conflicting results and eroded trust. Horizon Context provides a governed semantic foundation on your single data copy, so every agent, analyst and application works from the same definitions.

Connect metadata from source databases, BI tools and data pipelines into Horizon Catalog to give AI the complete picture of how data is defined, connected and used across your organization.
Build governed business definitions from your existing SQL, Tableau and Power BI models with Semantic View Autopilot and Semantic Studio. AI auto-generates documentation while humans stay in the loop.
AI agents, BI dashboards and apps automatically discover and use governed definitions. Snowflake CoCo, native BI integrations and open standards carry your business logic to any compatible tool.
customers

Affirm Achieves Data Sovereignty and Improves Performance
Affirm turned to Snowflake for its financial workloads to enhance operational efficiency and performance — without compromising flexibility and choice.

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