Key Takeaways
- Snowflake signs a $6 billion AWS agreement over 5 years
- Customer spending on AWS reached $2 billion in 2025
- Snowflake has sold $7 billion via AWS Marketplace since 2012
- Graviton chips gain traction in AI-driven cloud workloads
Snowflake has entered into a 6 billion agreement with Amazon Web Services over a period of 5 years, marking one of the largest cloud contracts tied to data infrastructure and artificial intelligence demand. The Snowflake AWS deal reflects rising enterprise spending on cloud platforms as AI workloads expand across industries.
AI demand accelerates cloud spending and infrastructure expansion
The agreement comes as Snowflake customers increase their usage of AWS services. The company reported that customer spending on AWS reached 2 billion dollars in 2025, representing a doubling within a single calendar year. Analysts say the Snowflake AWS deal signals growing confidence in long-term AI infrastructure investment.
Since its founding in 2012, Snowflake has generated 7 billion dollars in total sales through AWS Marketplace. The new agreement alone approaches that cumulative figure, highlighting the scale of current demand growth.
A key driver behind this increase is the adoption of AI tools within enterprise systems. Snowflake has developed its Cortex AI platform, which enables users to interact with data through natural language queries, generate summaries, and automate data analysis tasks.
As more companies deploy AI applications, demand for computing resources continues to rise. This includes both data storage and processing capacity required to support continuous AI operations.
The agreement also includes expanded access to AWS-developed processors known as Graviton. These processors are based on ARM architecture and are designed to handle a wide range of cloud computing tasks. Industry observers view the Snowflake AWS deal as part of a broader push toward optimized AI cloud infrastructure.
Chip competition intensifies as cloud providers expand capabilities
The inclusion of Graviton processors reflects a broader shift in how AI workloads are managed. While graphics processing units are used for training and advanced reasoning, central processing units handle a significant share of operational tasks, including automation and system coordination.
As AI applications move from development to daily use, demand for processing power increases across both types of chips. This has led cloud providers to expand their own chip development efforts.
Amazon has positioned its in-house processors as a cost-efficient option for cloud customers. These processors are deployed at scale within AWS infrastructure, contributing to the company’s ability to support large enterprise contracts tied to the Snowflake AWS deal.
Recent agreements indicate growing adoption of these processors. AWS signed a separate deal to supply millions of Graviton chips to a major technology company for AI computing needs. This followed another cloud agreement valued at 10 billion dollars with a competing provider.
Other cloud companies are also investing in proprietary chip development. Google has developed its own processors for several years, while Microsoft introduced a new AI chip earlier this year.
At the same time, established chip manufacturers continue to expand their offerings. A new processor introduced by a leading chip company targets a market estimated at 200 billion dollars, with reported sales of 20 billion dollars to date.
The increasing number of cloud agreements and chip investments reflects a competitive environment shaped by AI demand. Cloud providers, chip developers, and enterprise software companies are all expanding their capabilities to support growing computational requirements. The Snowflake AWS deal highlights how data platforms and cloud infrastructure are becoming closely integrated as businesses scale AI-driven operations.
The Snowflake and AWS agreement highlights how data platforms and cloud infrastructure are becoming closely integrated as businesses scale AI-driven operations.
