Executive summary
- Product revenue Q2 FY2026 $1,090.5 million; product revenue growth +32% YoY and dollar-based net revenue retention 125% as of July 31, 2025.
- Q2 FY2026 product gross profit $788.2 million; product gross margin ~72% and operating loss (GAAP) widened to reflect investments; free cash flow positive but volatile.
- Balance-sheet strength: cash, cash equivalents and investments ~$4.6 billion as of July 31, 2025; remaining performance obligations (RPO) ~$6.9 billion supporting revenue visibility.
- Valuation and multiples: enterprise value roughly $75–76 billion implying EV/Revenue in the high teens; valuation is heavily dependent on sustained data consumption and AI workload growth.
- Verdict: Snowflake stock data cloud growth 2025 is a constructive growth narrative-strong product revenue reacceleration, high retention and AI product momentum-but profitability and margin expansion remain execution-sensitive and exposed to competition and model-cost economics.
Summary fundamentals
- Latest quarter product revenue (Q2 FY2026): $1,090.5 million.
- Revenue YoY % (product): +32% year-over-year.
- Latest quarter GAAP EPS (Q2 FY2026): GAAP net loss per share reported (net income negative); non-GAAP EPS reported positive (refer to press release for exact per-share).
- EPS YoY change: improvement in non-GAAP operating income and EPS versus prior quarters despite GAAP net loss driven by investments.
- Product gross margin (Q2 FY2026): ~72% (product gross profit $788.2 million).
- Debt-to-equity: low nominal leverage; enterprise liquidity includes $4.6 billion in cash, cash equivalents and short-term and long-term investments.
- Market capitalization (late-Sept 2025 snapshot): approximately $75–76 billion.
Detailed fundamental analysis
Revenue trends
Snowflake’s product revenue accelerated to $1.0905 billion in Q2 FY2026, a 32% year-over-year increase that outperformed guidance and consensus. The growth is concentrated in product consumption-compute, storage and data transfer-reflecting enterprise migration of AI workloads and data modernization projects. Management reported 654 customers with trailing-12-month product revenue greater than $1 million, highlighting deepening account penetration.
RPO (remaining performance obligations) increased to roughly $6.9 billion, with management estimating about 50% of RPO will convert to revenue in the next 12 months-giving Snowflake predictable revenue runoff while still depending on additional consumption from existing customers to drive upside.
Margin drivers and profit dynamics
Product gross margin (~72%) is high for a consumption-based data platform, driven by efficient storage/compute provisioning and product mix. However, Snowflake’s consolidated operating income (GAAP) remains negative because the company continues to invest heavily in R&D, go-to-market expansion and AI product development (Cortex AI, Arctic models and partner integrations). Non-GAAP operating margins have improved and the company reported positive adjusted operating income in recent quarters, but converting product revenue growth into durable GAAP profitability depends on operating leverage and controlled investment pacing.
Model cost economics are a second-order margin risk: training and serving large language models or hosting inference workloads can push up cloud and GPU costs for customers and platform operators alike; Snowflake’s ability to monetize value (consumption fees, model hosting premiums) while managing infrastructure cost per request is central to margin expansion.
Balance-sheet strength and cash flow
As of July 31, 2025 Snowflake reported approximately $4.6 billion in cash, cash equivalents and short-term and long-term investments, giving management runway for product investment and selective M&A. Adjusted free cash flow in the quarter was positive but modest, and TTM free cash flow remains a critical watch item-Snowflake reported adjusted free cash flow of $67.8 million for the quarter, and TTM FCF improved but requires sustained margin expansion to normalize.
Valuation multiples
Snowflake’s market pricing (market cap ≈ $75–76 billion; EV roughly $75–76 billion) implies an EV/Revenue multiple in the high teens based on recent revenue run-rates and guidance; reported enterprise-value/revenue metrics are near 18x in public feeds. That multiple reflects high expectations for continued data consumption growth and AI workload monetization. Given Snowflake’s negative GAAP earnings and uneven GAAP profitability, investors should prefer EV/Revenue and EV/TTM-product-revenue frameworks to judge value.
Momentum & technical snapshot
- RSI(14): ~54.7 indicating neutral-to-constructive momentum on daily charts.
- MACD status: short-term MACD positive on multiple aggregators (MACD above signal), supporting momentum-based entries; intraday MACD can swing quickly.
- 50-day & 200-day SMA: 50-day SMA ≈ $214; 200-day SMA ≈ $187; current price trading above both averages in late-Sept 2025, indicating a medium-term uptrend.
- 1-month return vs Nasdaq: SNOW outperformed the Nasdaq Composite across the most recent earnings reaction window, driven by the Q2 beat and pro forma guidance raise.
- Average daily dollar volume: average daily shares traded ~3–5 million; at a ~$225 share price, average daily dollar volume approximates $700M–$1.1B-ample liquidity for institutional execution.
Technical takeaway: indicators are constructive following a strong earnings/guide print, but the stock’s high multiple makes it sensitive to any guidance softness or broader AI demand deceleration.
Peer comparison
Direct public peers and comparable data-platform names:
- Datadog Inc. (DDOG) – Q2 2025 revenue $827 million, +28% YoY; strong profittability on non-GAAP basis and product portfolio focused on observability for AI systems. Datadog’s operating leverage and gross margins are solid, but product exposure differs (telemetry vs data warehousing).
- MongoDB, Inc. (MDB) – Q2 FY2026 revenue $591.4 million, +24% YoY; Atlas cloud revenue +29% and cloud-consumption dynamics resemble Snowflake’s consumption model at a smaller scale. MongoDB’s margin profile and ARR dynamics provide a complementary benchmark for cloud-data monetization.
Comparison summary: Snowflake leads on scale and product revenue growth; Datadog and MongoDB offer alternative angles on AI workload monetization (observability and operational databases) and their margin/valuation tradeoffs help triangulate Snowflake’s relative fairness.
Latest earnings highlights & management guidance
- “Product revenue for the quarter was $1.09 billion, representing 32% year-over-year growth.”
- “Net revenue retention rate was 125% as of July 31, 2025.”
- “Remaining Performance Obligations were $6.9 billion as of July 31, 2025, with approximately 50% expected to be recognized in the next 12 months.”
- “Management raised full-year product revenue guidance to approximately $4.395 billion and expects third quarter product revenue between $1.125–$1.13 billion.”
All bullets are verbatim summary points from Snowflake’s Q2 FY2026 press release and investor materials.
Strategic moves, catalysts & risks
Strategic moves and catalysts
- Arctic LLM and embedding models: Snowflake launched Arctic (enterprise-grade LLM) and Arctic-embed family, positioning the company to capture both model hosting and retrieval-augmented workflows that drive consumption.
- Anthropic and third-party model partnerships: Snowflake’s multi-year Anthropic partnership (Claude family) and subsequent availability of Anthropic Sonnet models on Snowflake Cortex AI expand model choice for customers and increase premises for paid compute and inference consumption.
- Ecosystem & marketplace growth: Snowflake’s marketplace and partner integrations (NVIDIA NIM, model catalogs) accelerate developer adoption and can convert data assets into paid workloads.
Principal risks
- Competition and share-shift: entrenched rivals and well-funded private competitors (Databricks) and cloud provider services can pressure price and product differentiation. Market commentary repeatedly flags competition as a primary risk to long-term share gains.
- Model cost economics: customers scaling generative AI may face high GPU and inference costs, which could limit consumption or push price sensitivity onto Snowflake’s consumption model if Snowflake cannot preserve unit economics.
- Profitability execution risk: Snowflake’s valuation assumes continued high growth and eventual margin expansion; missed guidance, slower net new ARR or retention erosion would prompt rapid multiple compression given current EV/Revenue levels.
Valuation & scenario analysis
Inputs: market cap ≈ $75–76B, enterprise value ≈ $75–76B, Q2 product revenue $1.0905B, full-year product revenue guidance $4.395B (FY2026). Sources: company filings and market data.
Method: EV/Revenue applied to forward product revenue and blended product+services run-rates.
- Conservative scenario – Price target $98: Assumptions: product growth slows to mid-teens, market assigns EV/Revenue 8× to forward product revenue (~$4.4B), multiple compression due to margin risk and competition. Rationale: investor repricing if AI consumption growth weakens.
- Base scenario – Price target $185: Assumptions: management guidance validated, product revenue grows ~27% FY2026, market assigns EV/Revenue ~12–14× reflecting durable consumption growth and improving operating margins. Rationale: mixed valuation that prices in AI traction with moderate operating-leverage realization.
- Optimistic scenario – Price target $310: Assumptions: Snowflake sustains 30%+ product revenue growth, net revenue retention rises above 130%, and the market assigns 20×+ EV/Revenue driven by platform monopolization of enterprise AI data workloads. Rationale: requires execution on Arctic/Cortex, major enterprise contracts and defensible monetization.
Valuation caveat: scenarios are illustrative; real implied prices require up-to-date share counts, net cash, and enterprise-value calculations at execution time.
Trading checklist & signals
Momentum trader (short–medium term)
- Entry rule: buy on daily close above 50-day SMA with RSI between 50–70 and MACD crossing above signal; confirm with volume > 20-day average.
- Initial stop: 8% below entry; reduce position if price falls below 200-day SMA.
- Position sizing: 1–3% of portfolio – volatility and valuation demand conservative sizing.
Longer-term investor (fundamental)
- Sizing: limit SNOW to 0.5–2% of long-term equity allocation unless investor explicitly seeks high-growth AI-data exposure.
- Add criteria before meaningful allocation increase: (1) sustained product revenue growth consistent with guidance for two consecutive quarters, (2) net revenue retention ≥125% or rising, (3) improving non-GAAP operating margin and FCF conversion.
- Hedging: consider protective puts if position exceeds 1% of portfolio or use diversified exposure across data, observability and cloud platform names to reduce single-name execution risk.
