Snowflake and AWS Announce $6 Billion Partnership on Cloud Data Services

On May 27, 2026, Snowflake signed a multi-year agreement with Amazon Web Services committing $6 billion to AWS infrastructure. This is Snowflake's largest commitment to AWS yet, and it formalizes a deep partnership between the two companies. Most of Snowflake's customers already run on AWS, so the deal essentially locks in Snowflake's reliance on Amazon's cloud platform for the foreseeable future.

The partnership also includes joint work to optimize Snowflake's performance on AWS Graviton processors — custom chips that Amazon designs and manufactures itself. AWS released its latest version, Graviton4, in November 2023, and has been iterating on these chips for roughly five years.

What the $6 Billion Means

The commitment is large, though AWS and Snowflake did not disclose how many years it spans. It reflects Snowflake's confidence in its own growth and its belief that AWS is the right long-term home for its infrastructure needs.

For AWS, landing a $6 billion commitment from one of the fastest-growing data analytics companies is a significant win. AWS values partnerships like this — they signal that a major software company trusts Amazon's infrastructure enough to bet billions on it. In return, Snowflake gets priority treatment, favorable pricing, and access to AWS's newest services and hardware.

Optimizing for Custom Chips

A big part of the deal focuses on making Snowflake run better on Graviton processors. These chips are an alternative to the Intel and AMD processors that have traditionally powered data warehouses. AWS claims Graviton offers better value for the money — you get good performance per dollar spent.

For Snowflake, tighter optimization on Graviton could lower the cost of running its service, which means faster query responses and lower bills for customers — or better profit margins for Snowflake itself. Both companies are betting that ARM-based chips (the architecture Graviton uses) can handle data warehouse work just as well as the older x86 architecture, which is a shift in how the industry thinks about analytics.

The Bigger Picture

Snowflake faces real competition from Microsoft Azure Synapse, Google BigQuery, and newer tools built on open-source software. This AWS partnership gives Snowflake an advantage: it becomes harder and more expensive for customers to move their data to a rival cloud platform, since the infrastructure deal binds Snowflake tightly to Amazon's ecosystem.

The timing also matters. Cloud analytics is growing because enterprises are adopting artificial intelligence and machine learning — both hungry for computing power and storage. A company like Snowflake doesn't commit $6 billion unless it sees sustained customer demand ahead. The bet is that this infrastructure spend will pay off over time.

We have seen similar patterns in the past when major enterprise software companies made large-scale cloud commitments. Salesforce, for example, made comparable multi-billion-dollar AWS deals in the 2010s as companies shifted from running software in their own data centers to renting it from the cloud. Those early partnerships set a template for how software firms could negotiate favorable terms while offloading the burden of managing hardware.

How the Partnership Works

Beyond just paying for computing capacity, Snowflake and AWS are collaborating on technical integration — meaning engineers from both sides are working together to make sure Snowflake performs well on AWS's latest hardware. This is more than a simple vendor-customer relationship. AWS wants Snowflake to succeed on its platform because Snowflake customers use other AWS services too, creating a cycle that benefits Amazon.

Since Snowflake's core function is processing huge queries very efficiently, optimization at the chip level could unlock real performance gains. For a company running thousands of analytics queries a day, even modest improvements in speed and efficiency add up to substantial cost savings.

What Comes Next

This partnership sets up both companies to capture growing demand for cloud-based analytics and AI workloads. Snowflake gains infrastructure stability and the potential to improve its unit economics — the cost it pays to deliver service to each customer — through Graviton optimization. AWS locks in a large, multi-year revenue stream and gets proof that its custom silicon works well for serious analytics workloads.

The $6 billion commitment also sends a signal about Snowflake's own health and trajectory. Companies typically make infrastructure bets this large only when they have good visibility into future growth. A multi-year deal like this gives Snowflake predictable costs and priority access, while AWS gains revenue certainty.

As both companies invest more in AI and machine learning capabilities, this foundation could enable future collaboration on new workloads that demand substantial computing power and specialized performance characteristics.