Datadog (DDOG) Property, Plant & Equipment (Net) (2018 - 2026)
Datadog (DDOG) posted Property, Plant & Equipment (Net) of $438.17 million for Q3 2026, up 42.4% from $307.61 million a year earlier and up 7.0% from the prior quarter.
Datadog (DDOG) Property, Plant & Equipment (Net) (2018 - 2026) Analysis & Trends
At the end of FY2025, Datadog's Property, Plant & Equipment (Net) came in at $338.09 million, up 49.0% from FY2024.
- Annual Property, Plant & Equipment (Net) has increased for seven consecutive years, with a five-year compound annual growth rate of 48.3% (FY2020 to FY2025).
- In prior years, Datadog's Property, Plant & Equipment (Net) was $226.97 million in FY2024 (+32.1%), $171.87 million in FY2023 (+37.1%), $125.35 million in FY2022 (+66.8%) and $75.15 million in FY2021 (+59.2%).
- The Q3 2026 figure stands as the highest quarterly Property, Plant & Equipment (Net) in data going back to Q4 2018.
- On a year-over-year basis, Property, Plant & Equipment (Net) has increased in each of the last 21 quarters, with growth averaging 42.7% over the last eight quarters.
- Over the past five years, the year-over-year growth in Property, Plant & Equipment (Net) ranged from 31.8% (Q1 2024) to 71.8% (Q1 2022).
- According to Business Quant data, Property, Plant & Equipment (Net) for the three prior quarters was $409.63 million (Q2 2026), $378.94 million (Q1 2026) and $338.09 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn | 523.00 Mn |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn | 1.17 Bn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn | 207.98 Mn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn | 1.73 Bn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn | 438.17 Mn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn | 753.00 Mn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn | 33.00 Mn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn | 341.51 Mn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn | 38.99 Mn |
| 10 | Roku | 23.89 Bn | 13.92 Bn | 648.52 Mn | 143.21 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 438.17 Mn |
| Jun 30, 2026 | 409.63 Mn |
| Mar 31, 2026 | 378.94 Mn |
| Dec 31, 2025 | 338.09 Mn |
| Sep 30, 2025 | 307.61 Mn |
| Jun 30, 2025 | 283.08 Mn |
| Mar 31, 2025 | 249.92 Mn |
| Dec 31, 2024 | 226.97 Mn |
| Sep 30, 2024 | 215.81 Mn |
| Jun 30, 2024 | 198.91 Mn |
| Mar 31, 2024 | 182.42 Mn |
| Dec 31, 2023 | 171.87 Mn |
| Sep 30, 2023 | 157.69 Mn |
| Jun 30, 2023 | 145.10 Mn |
| Mar 31, 2023 | 138.40 Mn |
| Dec 31, 2022 | 125.35 Mn |
| Sep 30, 2022 | 110.89 Mn |
| Jun 30, 2022 | 97.79 Mn |
| Mar 31, 2022 | 90.71 Mn |
| Dec 31, 2021 | 75.15 Mn |
Datadog Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=DDOG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "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=property-plant-and-equipment-net&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();