Snowflake (SNOW) EBITDA (2019 - 2026)
Snowflake's (SNOW) quarterly EBITDA came in at -$263.0 million in Q3 2026, up 22.72% year-over-year from -$214.3 million in Q3 2025, and up 19.37% quarter-over-quarter from -$326.2 million in Q2 2026.
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Analysis
Snowflake (SNOW) EBITDA (2019 - 2026) Analysis & Trends
Snowflake has disclosed EBITDA across 8 years of filings, most recently posting -$263.0 million for Q3 2026.
- In Q3 2026, EBITDA rose 22.72% year-over-year to -$263.0 million; the TTM figure through Jul 2026 stood at -$1.2 billion (up 19.67% YoY), while the FY2026 annual figure was -$1.4 billion, up 1.43% from the prior year.
- EBITDA came in at -$263.0 million for Q3 2026 at Snowflake, up from -$326.2 million in the prior quarter.
- In the past five years, EBITDA ranged from a high of -$152.0 million in Q1 2022 to a low of -$447.3 million in Q2 2025.
- Average EBITDA over 5 years is -$293.1 million, with a median of -$285.4 million recorded in 2023.
- Year-over-year, EBITDA tumbled 57.7% in 2023 and rose 27.08% in 2026.
- Over 5 years, EBITDA stood at -$206.0 million in 2022, then decreased by 26.5% to -$260.6 million in 2023, then slumped by 40.22% to -$365.5 million in 2024, then climbed by 9.85% to -$329.5 million in 2025, then advanced by 20.19% to -$263.0 million in 2026.
- Per Business Quant data, the three most recent EBITDA figures were -$263.0 million in Q3 2026, -$326.2 million in Q2 2026, and -$318.2 million in Q1 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 320.54 Bn | 317.47 Bn | 2.30 Bn | 172.00 Mn |
| 2 | CrowdStrike Holdings | 268.77 Bn | 263.80 Bn | 1.10 Bn | -33.23 Mn |
| 3 | Fortinet | 131.12 Bn | 127.05 Bn | 1.64 Bn | 689.30 Mn |
| 4 | Snowflake | 118.02 Bn | 115.67 Bn | 1.04 Bn | -262.97 Mn |
| 5 | Datadog | 90.27 Bn | 85.29 Bn | 881.34 Mn | 5.46 Mn |
| 6 | Axon Enterprise | 36.61 Bn | 35.93 Bn | 546.45 Mn | 46.78 Mn |
| 7 | Zscaler | 34.97 Bn | 31.49 Bn | - | - |
| 8 | MongoDB | 34.51 Bn | 32.10 Bn | 569.77 Mn | 28.40 Mn |
| 9 | Okta | 34.32 Bn | 32.02 Bn | 641.00 Mn | 107.00 Mn |
| 10 | Baidu | 30.55 Bn | 8.15 Bn | 1.76 Mn | 906.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | -194.34 Mn |
| Apr 30, 2026 | -200.82 Mn |
| Jan 31, 2026 | -214.23 Mn |
| Oct 31, 2025 | -271.60 Mn |
| Jul 31, 2025 | -285.44 Mn |
| Apr 30, 2025 | -372.66 Mn |
| Jan 31, 2025 | -312.26 Mn |
| Oct 31, 2024 | -318.41 Mn |
| Jul 31, 2024 | -287.37 Mn |
| Apr 30, 2024 | -285.59 Mn |
| Jan 31, 2024 | -220.45 Mn |
| Oct 31, 2023 | -209.28 Mn |
| Jul 31, 2023 | -237.94 Mn |
| Apr 30, 2023 | -232.40 Mn |
| Jan 31, 2023 | -204.10 Mn |
| Oct 31, 2022 | -173.77 Mn |
| Jul 31, 2022 | -177.79 Mn |
| Apr 30, 2022 | -165.62 Mn |
| Jan 31, 2022 | -135.07 Mn |
| Oct 31, 2021 | -142.09 Mn |
API Access
Snowflake EBITDA 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=ebitda&ticker=SNOW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=SNOW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();