Datadog (DDOG) Capital Expenditures (2018 - 2026)
Datadog's Capital Expenditures was $9.89 million in Q2 2026, down 34.7% from $15.15 million a year earlier and down 12.9% from the prior quarter.
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Analysis
Datadog (DDOG) Capital Expenditures (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Datadog's Capital Expenditures was $46.93 million through Jun 30, 2026, up 17.2% year-over-year; for FY2025, it was $49.58 million, up 42.8% from FY2024.
- Capital Expenditures shows a five-year compound annual growth rate of 55.7% (FY2020 to FY2025).
- In earlier years, Capital Expenditures was $34.72 million in FY2024 (+25.9%), $27.59 million in FY2023 (-21.8%), $35.26 million in FY2022 (+254.2%) and $9.96 million in FY2021 (+83.9%).
- Quarterly Capital Expenditures has moved between $2.34 million (Q2 2023) and $16.79 million (Q3 2025) over five years.
- Compared with a year earlier, Capital Expenditures was higher in five of the last eight quarters, with growth averaging 40.8%.
- The best year-over-year quarter for Capital Expenditures over five years was Q1 2022 (growth of 853.3%); the worst was Q2 2023 (a decline of 60.9%).
- Per Business Quant data, DDOG's Capital Expenditures in the three quarters before Q2 2026 was $11.36 million (Q1 2026), $8.89 million (Q4 2025) and $16.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 103.00 Mn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 124.41 Mn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 78.00 Mn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 7.55 Mn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 9.89 Mn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 21.05 Mn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 2.47 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | 1.00 Mn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | - |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | -1.68 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.89 Mn |
| Mar 31, 2026 | 11.36 Mn |
| Dec 31, 2025 | 8.89 Mn |
| Sep 30, 2025 | 16.79 Mn |
| Jun 30, 2025 | 15.15 Mn |
| Mar 31, 2025 | 8.75 Mn |
| Dec 31, 2024 | 7.76 Mn |
| Sep 30, 2024 | 8.39 Mn |
| Jun 30, 2024 | 4.42 Mn |
| Mar 31, 2024 | 14.16 Mn |
| Dec 31, 2023 | 10.40 Mn |
| Sep 30, 2023 | 6.11 Mn |
| Jun 30, 2023 | 2.34 Mn |
| Mar 31, 2023 | 8.74 Mn |
| Dec 31, 2022 | 10.05 Mn |
| Sep 30, 2022 | 9.71 Mn |
| Jun 30, 2022 | 5.99 Mn |
| Mar 31, 2022 | 9.51 Mn |
| Dec 31, 2021 | 2.41 Mn |
| Sep 30, 2021 | 3.32 Mn |
API Access
Datadog Capital Expenditures 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=capital-expenditures&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "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=capital-expenditures&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();