Snowflake (SNOW) Other Operating Expenses (2019 - 2026)
Snowflake (SNOW) posted Other Operating Expenses of $1.18 billion for fiscal Q2 2027 (quarter ended Jul 31, 2026), up 18.9% from $991.83 million a year earlier and up 6.6% from the prior quarter.
Snowflake (SNOW) Other Operating Expenses (2019 - 2026) Analysis & Trends
For the trailing twelve months through Jul 31, 2026, Other Operating Expenses at Snowflake was $4.39 billion, up 21.3% year-over-year; for FY2026 (ended Jan 31, 2026), it was $3.92 billion, up 13.5% from FY2025.
- Annual Other Operating Expenses has increased for seven consecutive fiscal years, with a five-year compound annual growth rate of 40.5% (FY2021 to FY2026).
- In prior fiscal years, Snowflake's Other Operating Expenses was $3.46 billion in FY2025 (+29.0%), $2.68 billion in FY2024 (+41.4%), $1.89 billion in FY2023 (+56.5%) and $1.21 billion in FY2022 (+68.8%).
- The fiscal Q2 2027 figure stands as the highest quarterly Other Operating Expenses in data going back to fiscal Q3 2020.
- On a year-over-year basis, Other Operating Expenses has increased in each of the last 24 quarters, with growth averaging 20.2% over the last eight quarters.
- Over the past five years, the year-over-year growth in Other Operating Expenses ranged from 1.6% (fiscal Q1 2026) to 67.1% (fiscal Q4 2023).
- According to Business Quant data, Other Operating Expenses for the three prior fiscal quarters was $1.11 billion (Q1 2027), $1.06 billion (Q4 2026) and $1.04 billion (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn |
| 10 | Roku | 23.89 Bn | 13.92 Bn | 648.52 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 611.62 Mn |
| Apr 30, 2026 | 588.95 Mn |
| Jan 31, 2026 | 551.26 Mn |
| Oct 31, 2025 | 550.36 Mn |
| Jul 31, 2025 | 501.96 Mn |
| Apr 30, 2025 | 458.55 Mn |
| Jan 31, 2025 | 432.68 Mn |
| Oct 31, 2024 | 437.96 Mn |
| Jul 31, 2024 | 400.63 Mn |
| Apr 30, 2024 | 400.82 Mn |
| Jan 31, 2024 | 361.82 Mn |
| Oct 31, 2023 | 355.08 Mn |
| Jul 31, 2023 | 343.29 Mn |
| Apr 30, 2023 | 331.56 Mn |
| Jan 31, 2023 | 303.47 Mn |
| Oct 31, 2022 | 284.48 Mn |
| Jul 31, 2022 | 274.65 Mn |
| Apr 30, 2022 | 243.91 Mn |
| Jan 31, 2022 | 203.29 Mn |
| Oct 31, 2021 | 190.97 Mn |
Snowflake Other 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=other-operating-expenses&ticker=SNOW&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-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=other-operating-expenses&ticker=SNOW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();