Datadog (DDOG) EBITDA (2018 - 2026)
Datadog (DDOG) recorded EBITDA of $119.3 million in Q3 2026, up 349.5% from $26.54 million a year earlier and up 153.6% from the prior quarter.
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Analysis
Datadog (DDOG) EBITDA (2018 - 2026) Analysis & Trends
On a TTM basis, Datadog's EBITDA came in at $256.6 million as of Sep 30, 2026, up 252.3% year-over-year; for FY2025, it was $78.18 million, down 51.5% from FY2024.
- Annual EBITDA has a five-year compound annual growth rate of 30.8% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $161.26 million in FY2024 (+221.2%), $50.21 million in FY2023, $3.94 million in FY2022 (-81.8%) and $21.68 million in FY2021 (+6.3%).
- The Q3 2026 figure is the highest quarterly EBITDA in data going back to Q4 2018.
- On a year-over-year basis, EBITDA rose in three of the last six quarters, with growth averaging 77.6%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 521.6% in Q4 2021, against a decline of 62.6% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $47.04 million (Q2 2026), $45.58 million (Q1 2026) and $44.69 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn | 693.00 Mn |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn | 170.34 Mn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn | -134.60 Mn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn | 843.00 Mn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn | 119.30 Mn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn | 93.76 Mn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn | 166.00 Mn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn | 79.24 Mn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn | 35.33 Mn |
| 10 | Roku | 23.89 Bn | 13.92 Bn | 648.52 Mn | 178.29 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 119.30 Mn |
| Jun 30, 2026 | 47.04 Mn |
| Mar 31, 2026 | 45.58 Mn |
| Dec 31, 2025 | 44.69 Mn |
| Sep 30, 2025 | 26.54 Mn |
| Jun 30, 2025 | -6.78 Mn |
| Mar 31, 2025 | 13.74 Mn |
| Dec 31, 2024 | 39.35 Mn |
| Sep 30, 2024 | 47.67 Mn |
| Jun 30, 2024 | 37.56 Mn |
| Mar 31, 2024 | 36.74 Mn |
| Dec 31, 2023 | 50.76 Mn |
| Sep 30, 2023 | 17.58 Mn |
| Jun 30, 2023 | -2.06 Mn |
| Mar 31, 2023 | -16.05 Mn |
| Dec 31, 2022 | -16.76 Mn |
| Sep 30, 2022 | -14.73 Mn |
| Jun 30, 2022 | 11.58 Mn |
| Mar 31, 2022 | 23.83 Mn |
| Dec 31, 2021 | 20.67 Mn |
API Access
Datadog 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=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "DDOG", "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=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();