Snowflake is set to report its latest quarterly results after the closing bell on Wednesday, with the cloud database software provider's stock seen potentially rising to a fresh five-year high following the results.
Snowflake heads into Q2 earnings with strong AI momentum and customer growth, though premium valuation and margin pressures remain risks.
Beyond analysts' top-and-bottom-line estimates for Snowflake (SNOW), evaluate projections for some of its key metrics to gain a better insight into how the business might have performed for the quarter ended July 2026.
Snowflake's product revenues jump 34% to $1.33B as AI adoption and customer growth drive a higher fiscal 2027 revenue outlook.
Snowflake NYSE: SNOW CEO Sridhar Ramaswamy said enterprise AI is shifting attention away from model benchmarks and toward the quality, governance and business context of the underlying data.
Snowflake (NYSE:SNOW | SNOW Price Prediction) reports its next quarter on Wednesday, September 2, 2026, after the market closes, and the stock walks in hot.
Snowflake Inc. (SNOW) closed the most recent trading day at $322.78, moving 3% from the previous trading session.
SNOW's AI-driven products fuel 34% product revenue growth, while new model-routing capabilities strengthen its enterprise AI push.
The recommendations of Wall Street analysts are often relied on by investors when deciding whether to buy, sell, or hold a stock. Media reports about these brokerage-firm-employed (or sell-side) analysts changing their ratings often affect a stock's price.
SNOW's AI adoption is growing rapidly, but Dell Technologies' stronger earnings momentum, AI server demand and diversified drivers may offer greater upside.
In the most recent trading session, Snowflake Inc. (SNOW) closed at $325.5, indicating a -1.4% shift from the previous trading day.
UBS is telling clients that artificial intelligence is translating into real, growing spend on Snowflake, and the bank remains Buy-rated on the stock heading into its fiscal second-quarter results on September 2. The bank's analysts spoke with seven enterprise partners and customers to gauge demand trends, adoption of Snowflake's Cortex Code and Coco tools, and the risk that large language models could eat into spending on established data software vendors.