Snowflake inks $6B AWS deal centered on Graviton chips

Snowflake has entered into a five-year, $6 billion commitment with Amazon Web Services, marking the largest expansion in their 11-year partnership. The deal, announced Tuesday, includes a pledge to run workloads on AWS Graviton, Amazon’s custom Arm-based processor, and to deepen product integrations for what Snowflake calls “agentic enterprise” workloads.

This agreement represents a significant leap in Snowflake’s AWS spending trajectory. The company committed $1.2 billion at its 2020 IPO, which grew to $2.5 billion in a 2023 renewal. The new $6 billion commitment is roughly five times the 2020 figure and 2.4 times the 2023 one. The expansion mirrors Snowflake’s own growth: the company posted Q1 fiscal-2027 earnings on Wednesday that beat estimates substantially, and the stock jumped roughly 38% on the combined earnings and AWS-deal news.

The Graviton component is strategically crucial. AWS Graviton, now in its fourth generation, is Amazon’s in-house Arm-server processor line, designed to replace x86 chips from Intel and AMD with better price-performance. Snowflake committing to run its data-cloud workloads on Graviton at scale is a meaningful endorsement of the Arm-server thesis that has been reshaping cloud-infrastructure economics for five years. It also provides a useful data point for Amazon amid news that ByteDance is building its own Arm and RISC-V CPUs to escape Intel and AMD pricing pressure. The migration to custom Arm-server silicon, led by hyperscalers, is now the structural story in data-centre CPUs.

For AWS, the Snowflake deal lands within a stretch of large AI-infrastructure commitments. Anthropic has committed to large AWS spending over multi-year terms; OpenAI signed a meaningful Microsoft Azure-competitor agreement on AWS earlier this year; Meta has been visibly expanding its AWS footprint for inference workloads. Snowflake is the latest in that sequence and the largest non-foundation-model commitment on the list. AWS’s capacity to absorb $6 billion of additional five-year demand against an already-stretched data-centre pipeline is a useful indicator of how rapidly Amazon is bringing new capacity online.

The strategic context for Snowflake is the agentic-AI thesis the company has been betting on. Snowflake’s pitch, like that of every enterprise-data-platform vendor at scale, is that AI agents will operate primarily over the trusted, governed enterprise data already inside customers’ cloud-warehouse environments, rather than over external training corpora. Building that future requires substantially more compute integration with the underlying cloud provider, direct access to AWS’s native AI primitives (Bedrock, SageMaker, the Q assistant), and deeper marketplace and go-to-market integration.

The remaining open question is the Databricks comparison. Snowflake’s most visible competitor is more directly bundled with Azure through its 2023 Microsoft partnership and has been positioning aggressively on multi-cloud agnosticism. Snowflake’s deeper AWS commitment, including the explicit Graviton anchor, signals a different strategic bet: pick the larger hyperscaler partner, lock in customer-acquisition flow through AWS Marketplace, and accept the implicit single-cloud tilt that comes with it. Whether that pays off against Databricks’s diversification posture is the multi-year question. AWS Marketplace sales for Snowflake doubled year-on-year to $2 billion in 2025, which suggests the integration logic is already working commercially.

Neither company disclosed which specific Graviton generation Snowflake is committing to. Snowflake CEO Sridhar Ramaswamy said the company will publish more detail at the AWS re:Invent conference later this year.