Snowflake Inc.
Snowflake's mission is to empower every enterprise to achieve its full potential through data and AI. The company provides a cloud-based data platform that separates compute from storage, allowing organizations to unify data warehousing, data lakes, data engineering, and data sharing into a single service.
At a Glance
- Global enterprises
- Financial Services
- Healthcare & Life Sciences
- Retail & Consumer Goods
- +11 more
AI Tools by Snowflake Inc.
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Snowflake Cortex AI
AI Services for Snowflake Data
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Latest News
Snowflake and Anthropic Announce $200 Million Partnership to Bring Agentic AI to Global Enterprises
Accenture and Snowflake Drive Enterprise Reinvention with AI and Data
Snowflake Doubles AWS Marketplace Growth YoY, Eclipses $2 Billion in Sales
Snowflake Reports Financial Results for the Third Quarter of Fiscal 2026
Products & Services
Cloud-based data platform that separates compute from storage for scalable, on-demand analytics across AWS, Azure, and Google Cloud
Developer framework providing libraries for querying and transforming data at scale in Python, Scala, and Java, enabling code execution directly within Snowflake
Continuous data ingestion service for real-time data loading
Platform for discovering, accessing, and sharing data sets and applications; reached 3,400 marketplace listings as of July 2025
Market Position
Snowflake differentiates itself through a unique cloud-native architecture that completely separates compute from storage, enabling dynamic and scalable data storage and analytics. Unlike traditional data warehouses and competitors like Databricks, Snowflake offers a fully managed SaaS platform requiring less maintenance and infrastructure management. The company positioned itself as democratizing access to data analytics for businesses of all sizes. At launch, it took aim at Amazon and Hadoop, and more recently has competed with Databricks (both companies reached ~$5B ARR). Snowflake's multi-cloud strategy (AWS, Azure, GCP) provides unique interoperability and freedom, positioning it as the cornerstone for customers' data and AI strategies.
Leadership
Founders
Benoit Dageville
Previously worked as a data architect at Oracle Corporation from January 2002 to July 2012, including as Architect in the Manageability Group. Holds B.S., M.S., and Ph.D. degrees in Computer Science from Jussieu University.
Thierry Cruanes
Previously worked as a data architect at Oracle Corporation. Co-founder and currently serves as CTO of Snowflake.
Marcin Zukowski
Co-founder of Vectorwise, a database company that was acquired by Actian.
Executive Team
Sridhar Ramaswamy
Chief Executive Officer and Director
Previously served as Senior Vice President of AI at Snowflake (June 2023-Feb 2024), CEO of Neeva Inc. (2019-2023), Venture Partner at Greylock Partners (2018-2024), and SVP of Ads & Commerce at Google (2013-2018). Holds B.S. in Computer Science from Indian Institute of Technology Madras and M.S. and Ph.D. in Computer Science from Brown University.
Benoit Dageville
Co-Founder, President of Products and Director
Co-founder who previously served as CTO (2012-2019). Previously worked as Architect at Oracle Corporation (2002-2012). Holds B.S., M.S., and Ph.D. degrees in Computer Science from Jussieu University.
Board of Directors
Founding Story
Founded in July 2012 in San Mateo, California, Snowflake was created by three data warehousing experts who witnessed firsthand the limitations of traditional on-premise and cloud data platforms regarding scalability and complex management. They envisioned a data warehouse built for the cloud from the ground up that could leverage the flexibility of cloud compute and storage. Sutter Hill Ventures provided early funding, and venture capitalist Mike Speiser served as the company's first part-time CEO and CFO from August 2012 to June 2014. The company operated in stealth mode until October 2014, with its first product launched in June 2015.
Business Model
Revenue Model
Consumption-based model where revenue is recognized based on platform consumption of compute, storage, and data transfer resources. Customers can purchase via On-Demand or pre-paid capacity commitments with flexibility to consume more than contracted capacity.
Pricing Tiers
Core platform functionality with fully managed elastic compute, automatic encryption of all data, Snowpark, data sharing, and optimized storage with compression and Time Travel
All Standard features plus multi-cluster compute, granular governance and privacy controls, and extended Time Travel windows
All Enterprise features plus Tri-Secret Secure, access to private connectivity, and failover and failback for backup and disaster recovery
All Business Critical features in a completely separate, isolated Snowflake environment
Target Markets
- Global enterprises
- Financial Services
- Healthcare & Life Sciences
- Retail & Consumer Goods
- Technology companies
- Manufacturing
- Data warehousing and analytics
- Data lakes and multi-structured data management
- Machine learning and artificial intelligence
- Data security and governance
- Business intelligence and analytics
- Real-time data ingestion and processing
- Adobe
- Sony
- Capital One
- Cisco