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Snowflake Posts Record Q1 Revenue, Stock Surges

Snowflake reported $1.39 billion in revenue for the first quarter of fiscal 2027, a 33% year-over-year increase, with product revenue reaching $1.33 billion. The company also announced a $6 billion multi-year infrastructure commitment with Amazon Web Services centered on Graviton AI chips, and shares surged roughly 36% in after-hours trading. The results reflect 126% net revenue retention and 779 customers with trailing 12-month product revenue above $1 million, signaling strong enterprise AI spending on data platform expansions.

read3 min publishedMay 28, 2026

InvestorIdeas reports that Snowflake posted $1.39 billion in revenue for Q1 fiscal 2027, a 33% year-over-year increase, with product revenue of $1.33 billion, up 34% YoY. InvestorIdeas reports net revenue retention at 126%, 779 customers with trailing 12-month product revenue above $1 million, and remaining performance obligations of $9.21 billion, up 38% YoY. The company's CEO Sridhar Ramaswamy and CFO Brian Robins provided comments in the earnings release quoted by InvestorIdeas. SPXGamma Edge and FXLeaders report a $6 billion multi-year AWS infrastructure commitment centered on Graviton AI chips. SPXGamma Edge and market reports show Snowflake shares jumped roughly 36% in extended trading on the results and the AWS deal. SPXGamma Edge characterises the quarter as a platform re-rating and highlights the Natoma MCP acquisition as positioning Snowflake inside the enterprise AI agent stack.

What happened

Per InvestorIdeas, Snowflake reported $1.39 billion in revenue for the first quarter of fiscal 2027 (ended April 30, 2026), a 33% year-over-year increase, with $1.33 billion in product revenue, up 34% YoY. InvestorIdeas reports net revenue retention of 126%, 779 customers spending more than $1 million on a trailing 12-month basis (up 29% YoY), and remaining performance obligations of $9.21 billion (+38% YoY). InvestorIdeas published direct quotes from CEO Sridhar Ramaswamy and CFO Brian Robins in the company release. Market coverage from SPXGamma Edge and FXLeaders reports a roughly $6 billion multi-year AWS infrastructure commitment centred on Graviton AI chips; those outlets also reported a roughly 36% after-hours surge in Snowflake shares following the results.

Technical details

Editorial analysis - technical context: Public reporting frames the AWS commitment as focused on AI compute infrastructure, specifically mentioning Graviton-based capacity in SPXGamma Edge and FXLeaders coverage. For practitioners, an increase in dedicated cloud AI compute capacity from a hyperscaler partner typically reduces friction for large-context model deployments and vector-index workloads, and can widen options for colocated inference and data gravity patterns.

Context and significance

The combination of accelerating product revenue, a high 126% net revenue retention metric, and multi-year infrastructure commitments is being read by market commentators as validation of enterprise AI spending continuing to fund data platform expansions. Reporting by SPXGamma Edge places Snowflake's Natoma MCP acquisition in the same enterprise agent ecosystem targeted by vendors such as Anthropic and OpenAI, framing this quarter as part of a broader re-rating for AI infrastructure providers.

What to watch

For practitioners: monitor how the reported AWS capacity commitment is documented by AWS and Snowflake, specifically, scope, timeline, and Graviton vs GPU mix, since those details determine workload fit for training, fine-tuning, or inference. Also watch customer case studies and product telemetry around Cortex Code and Snowflake Intelligence adoption, which InvestorIdeas highlighted in CEO remarks as drivers of first-party AI product uptake. Finally, follow guidance updates and contract-level disclosures that clarify how much of the reported $9.21 billion RPO is AI-specific versus core data platform expansion.

Scoring Rationale #

Snowflake is a major enterprise data platform; a beat with accelerating product revenue, high net-retention, and a reported multi-billion AWS commitment materially affects infrastructure planning and vendor selection. This is notable for practitioners integrating data platforms with AI workloads.

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