Datadog (DDOG) Research & Development (2018 - 2026)
Datadog (DDOG) recorded Research & Development of $491.57 million in Q3 2026, up 22.3% from $401.98 million a year earlier and up 2.8% from the prior quarter.
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Analysis
Datadog (DDOG) Research & Development (2018 - 2026) Analysis & Trends
On a TTM basis, Datadog's Research & Development came in at $1.82 billion as of Sep 30, 2026, up 26.0% year-over-year; for FY2025, it was $1.55 billion, up 34.3% from FY2024.
- Annual Research & Development has increased for eight straight years, with a five-year compound annual growth rate of 49.0% (FY2020 to FY2025).
- Across earlier years, Research & Development came in at $1.15 billion in FY2024 (+19.8%), $962.45 million in FY2023 (+27.9%), $752.35 million in FY2022 (+79.2%) and $419.77 million in FY2021 (+99.3%).
- The Q3 2026 figure is the highest quarterly Research & Development in data going back to Q3 2018.
- On a year-over-year basis, Research & Development has increased for 25 consecutive quarters, with growth averaging 29.4% over the last eight quarters.
- The year-over-year growth in Research & Development has ranged between 14.7% (Q2 2024) and 96.5% (Q4 2021) over the last five years.
- Per Business Quant, the preceding three quarters came in at $477.97 million (Q2 2026), $435.3 million (Q1 2026) and $417.93 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn | 779.00 Mn |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn | 444.20 Mn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn | 567.48 Mn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn | 213.40 Mn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn | 491.57 Mn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn | 241.48 Mn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn | 163.00 Mn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn | 208.69 Mn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn | 213.87 Mn |
| 10 | Roku | 23.89 Bn | 13.92 Bn | 648.52 Mn | 186.87 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 491.57 Mn |
| Jun 30, 2026 | 477.97 Mn |
| Mar 31, 2026 | 435.30 Mn |
| Dec 31, 2025 | 417.93 Mn |
| Sep 30, 2025 | 401.98 Mn |
| Jun 30, 2025 | 387.48 Mn |
| Mar 31, 2025 | 341.06 Mn |
| Dec 31, 2024 | 316.31 Mn |
| Sep 30, 2024 | 291.80 Mn |
| Jun 30, 2024 | 274.60 Mn |
| Mar 31, 2024 | 269.99 Mn |
| Dec 31, 2023 | 253.25 Mn |
| Sep 30, 2023 | 240.23 Mn |
| Jun 30, 2023 | 239.49 Mn |
| Mar 31, 2023 | 229.48 Mn |
| Dec 31, 2022 | 218.66 Mn |
| Sep 30, 2022 | 205.39 Mn |
| Jun 30, 2022 | 177.70 Mn |
| Mar 31, 2022 | 150.61 Mn |
| Dec 31, 2021 | 133.05 Mn |
API Access
Datadog Research & Development 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=research-and-development&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "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=research-and-development&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();