Snowflake named a Leader in

the inaugural 2026 Gartner®

Magic Quadrant™ for

Data Lakehouse Platforms

We're proud to be recognized as a Leader in the first-ever Gartner Magic Quadrant for Data Lakehouse Platforms.

The Agentic Control Plane

Your data lives across platforms, systems of record and storage layers, spread across clouds and regions. Teams spend time moving it just to work on it, and every move breaks governance and meaning, adding cost and risk to agentic workflows. Snowflake's AI Data Cloud unifies it all into one fully interoperable lakehouse architecture, eliminating data movement and vendor lock-in so you can safely orchestrate multi-agent workflows across your enterprise data estate.

Download your complimentary copy to learn:

• What a data lakehouse platform needs to deliver
  
• How Gartner evaluates vendors on Completeness of Vision and Ability to Execute
  
• The strengths and cautions of each vendor in the market

FAQ
What is a data lakehouse?
A data lakehouse combines the low-cost, open storage of a data lake with the governance, performance and SQL analytics of a data warehouse. Teams can run analytics, data science and AI on one copy of data instead of maintaining separate systems.

What is an Apache Iceberg table?
Apache Iceberg is an open table format that lets multiple engines, such as Snowflake, Spark and Trino, read and write the same tables in your own cloud storage. It adds reliable transactions, schema evolution and time travel to files in a data lake.

What is the Gartner Magic Quadrant for Data Lakehouse Platforms?
It is Gartner's first evaluation of vendors in the data lakehouse platform market. Vendors are assessed on Completeness of Vision and Ability to Execute. Download the complimentary report above to see the full evaluation.

How does Snowflake support an open lakehouse?
Snowflake supports Apache Iceberg tables in Snowflake storage or your own cloud storage. It connects to external Iceberg catalogs through Catalog-Linked Databases. Horizon Catalog, built on Apache Polaris, governs those tables across engines.

Can I use Snowflake without moving my data?
Yes. Snowflake can query and govern data where it already lives, including Iceberg tables managed in other catalogs. Zero-copy sharing gives teams and partners access without duplicating data or building ETL pipelines.

How does Snowflake govern data across engines and clouds?
Horizon Catalog applies one set of access controls and policies to data across open table formats, Snowflake and external engines. Governance is enforced when data is queried, so policies stay consistent no matter which engine reads the table.

Why does interoperability matter for AI?
AI agents need fresh, trusted data with consistent meaning. When data has to be copied between systems, governance and context break and costs rise. An interoperable lakehouse lets agents work on governed data where it lives.

Is the Gartner report complimentary?
Yes. Complete the form above for complimentary access to the full report.

Gartner, Magic Quadrant for Data Lakehouse Platforms, Aaron Rosenbaum, Michael Gonzales et al., 4 November 2026.

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Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Snowflake.