Snowflake (SNOW) Operating Expenses (2019 - 2026)
Snowflake's Operating Expenses was $1.3 billion in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 16.7% from $1.11 billion a year earlier and up 3.8% from the prior quarter.
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Analysis
Snowflake (SNOW) Operating Expenses (2019 - 2026) Analysis & Trends
On a trailing twelve-month basis, Snowflake's Operating Expenses was $4.88 billion through Jul 31, 2026, up 14.0% year-over-year; for FY2026 (ended Jan 31, 2026), it was $4.58 billion, up 18.4% from FY2025.
- Operating Expenses has now increased for seven consecutive fiscal years, with a five-year compound annual growth rate of 38.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $3.87 billion in FY2025 (+28.8%), $3 billion in FY2024 (+37.1%), $2.19 billion in FY2023 (+48.4%) and $1.48 billion in FY2022 (+65.2%).
- The fiscal Q2 2027 figure marks the highest quarterly Operating Expenses in data going back to fiscal Q3 2020.
- Compared with a year earlier, Operating Expenses has increased for 24 straight quarters, with growth averaging 19.9% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 9.8% (fiscal Q1 2027) and 55.1% (fiscal Q4 2023) over the last five years.
- Per Business Quant data, SNOW's Operating Expenses in the three fiscal quarters before Q2 2027 was $1.25 billion (Q1 2027), $1.18 billion (Q4 2026) and $1.15 billion (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 264.72 Bn | 249.79 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 238.73 Bn | 219.14 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 127.27 Bn | 113.20 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 110.23 Bn | 97.55 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 89.17 Bn | 70.81 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 33.92 Bn | 20.04 Bn | - | - |
| 7 | Okta | 33.82 Bn | 23.92 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 33.04 Bn | 27.56 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 27.87 Bn | 18.34 Bn | 569.77 Mn | 541.37 Mn |
| 10 | F5 | 25.05 Bn | 19.46 Bn | 711.51 Mn | 498.25 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 1.30 Bn |
| Apr 30, 2026 | 1.25 Bn |
| Jan 31, 2026 | 1.18 Bn |
| Oct 31, 2025 | 1.15 Bn |
| Jul 31, 2025 | 1.11 Bn |
| Apr 30, 2025 | 1.14 Bn |
| Jan 31, 2025 | 1.04 Bn |
| Oct 31, 2024 | 986.66 Mn |
| Jul 31, 2024 | 936.05 Mn |
| Apr 30, 2024 | 904.76 Mn |
| Jan 31, 2024 | 808.40 Mn |
| Oct 31, 2023 | 765.85 Mn |
| Jul 31, 2023 | 741.03 Mn |
| Apr 30, 2023 | 687.42 Mn |
| Jan 31, 2023 | 623.11 Mn |
| Oct 31, 2022 | 572.33 Mn |
| Jul 31, 2022 | 531.75 Mn |
| Apr 30, 2022 | 463.21 Mn |
| Jan 31, 2022 | 401.62 Mn |
| Oct 31, 2021 | 370.93 Mn |
API Access
Snowflake Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=SNOW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SNOW", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SNOW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();