Snowflake jumps 40% after earnings beat, $6B AWS deal

On May 28, 2026, Snowflake shares jumped about 40%, erasing a roughly 20% year-to-date decline in a single session. The stock rise followed a quarterly earnings beat, a five-year $6 billion agreement with Amazon Web Services and a planned acquisition of Natoma.

The company reported fiscal first-quarter 2027 revenue of $1.39 billion, up 33% year over year and above a $1.32 billion consensus. Product revenue increased 34% to $1.33 billion; CEO Sridhar Ramaswamy described that as the largest sequential dollar increase the company has recorded. Non-GAAP earnings were $0.39 per share versus $0.32 expected. Net revenue retention remained at 126% and remaining performance obligations rose 38% to $9.21 billion.

Management raised full-year fiscal 2027 product revenue guidance to $5.84 billion, implying roughly 31% growth compared with a prior outlook near 27%.

The five-year, $6 billion agreement with AWS covers use of AWS Graviton processors for general workloads and GPU-accelerated EC2 instances for training AI models. The companies said the deal includes deeper integrations for agentic AI infrastructure, coordination on workload migrations and expanded joint sales through the AWS Marketplace. Snowflake noted lifetime sales on that marketplace have exceeded $7 billion.

Snowflake also announced plans to acquire Natoma, an enterprise Model Context Protocol platform that governs AI agents. The company said integrating Natoma will extend its agentic AI stack into identity and connectivity layers and enable customers to enrich Snowflake data with application context and take actions directly from Snowflake Intelligence and Cortex Code.

Ramaswamy wrote on X: “Once closed, @Snowflake users will be able to enrich their Snowflake data with critical application context and take action directly from Snowflake Intelligence and Cortex Code.”

Research firm Bull Theory described Snowflake as “the data infrastructure that AI runs on.” Analysts noted future revenue performance will depend on whether AI workloads convert into sustained consumption revenue and on the pace at which enterprise customers deploy agentic AI.