Datadog (DDOG) Other Non-Current Assets (2018 - 2026)
Datadog (DDOG) recorded Other Non-Current Assets of $145.03 million in Q2 2026, up 51.8% from $95.57 million a year earlier and up 6.4% from the prior quarter.
Datadog (DDOG) Other Non-Current Assets (2018 - 2026) Analysis & Trends
At the end of FY2025, Datadog reported Other Non-Current Assets of $126.71 million, up 46.4% from FY2024.
- Annual Other Non-Current Assets has increased for seven straight years, with a five-year compound annual growth rate of 36.5% (FY2020 to FY2025).
- Across earlier years, Other Non-Current Assets came in at $86.57 million in FY2024 (+17.4%), $73.73 million in FY2023 (+33.2%), $55.34 million in FY2022 (+31.6%) and $42.06 million in FY2021 (+57.2%).
- The Q2 2026 figure is the highest quarterly Other Non-Current Assets in data going back to Q4 2018.
- On a year-over-year basis, Other Non-Current Assets has increased for 20 consecutive quarters, with growth averaging 34.2% over the last eight quarters.
- Across the past five years, year-over-year growth in Other Non-Current Assets ran from 17.4% in Q4 2024 to 57.2% in Q4 2021.
- Per Business Quant, the preceding three quarters came in at $136.26 million (Q1 2026), $126.71 million (Q4 2025) and $105.94 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Other Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 678.00 Mn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 805.54 Mn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 113.30 Mn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 431.03 Mn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 145.03 Mn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 457.14 Mn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 327.95 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | 331.00 Mn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | 402.42 Mn |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | 25.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 145.03 Mn |
| Mar 31, 2026 | 136.26 Mn |
| Dec 31, 2025 | 126.71 Mn |
| Sep 30, 2025 | 105.94 Mn |
| Jun 30, 2025 | 95.57 Mn |
| Mar 31, 2025 | 90.50 Mn |
| Dec 31, 2024 | 86.57 Mn |
| Sep 30, 2024 | 80.00 Mn |
| Jun 30, 2024 | 77.04 Mn |
| Mar 31, 2024 | 73.07 Mn |
| Dec 31, 2023 | 73.73 Mn |
| Sep 30, 2023 | 62.98 Mn |
| Jun 30, 2023 | 60.51 Mn |
| Mar 31, 2023 | 56.64 Mn |
| Dec 31, 2022 | 55.34 Mn |
| Sep 30, 2022 | 50.15 Mn |
| Jun 30, 2022 | 46.84 Mn |
| Mar 31, 2022 | 42.75 Mn |
| Dec 31, 2021 | 42.06 Mn |
| Sep 30, 2021 | 35.51 Mn |
Datadog Other Non-Current Assets 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=other-non-current-assets&ticker=DDOG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-non-current-assets", "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=other-non-current-assets&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();