Datadog (DDOG) Change in Accured Expenses (2018 - 2026)
Datadog's Change in Accured Expenses came in at $6.98 million for Q2 2026, compared with -$3.25 million a year earlier.
Datadog (DDOG) Change in Accured Expenses (2018 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Datadog reported Change in Accured Expenses of $53.59 million, up 222.3% year-over-year; for FY2025, it was $52.89 million.
- Change in Accured Expenses carries a five-year compound annual growth rate of 67.8% (FY2020 to FY2025).
- Going back by year, Change in Accured Expenses was -$1.63 million in FY2024, -$40.49 million in FY2023, $37.58 million in FY2022 (+0.8%) and $37.27 million in FY2021 (+838.8%).
- The five-year range for quarterly Change in Accured Expenses is -$28.08 million (Q1 2023) to $31.66 million (Q3 2022).
- Business Quant data shows DDOG's Change in Accured Expenses at -$3.88 million (Q1 2026), $20.48 million (Q4 2025) and $30.01 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 369.00 Mn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 72.38 Mn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 75.10 Mn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 108.85 Mn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 6.98 Mn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 256.58 Mn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 43.09 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | -2.00 Mn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | - |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.98 Mn |
| Mar 31, 2026 | -3.88 Mn |
| Dec 31, 2025 | 20.48 Mn |
| Sep 30, 2025 | 30.01 Mn |
| Jun 30, 2025 | -3.25 Mn |
| Mar 31, 2025 | 5.65 Mn |
| Dec 31, 2024 | 4.08 Mn |
| Sep 30, 2024 | 10.15 Mn |
| Jun 30, 2024 | -8.42 Mn |
| Mar 31, 2024 | -7.43 Mn |
| Dec 31, 2023 | 27.75 Mn |
| Sep 30, 2023 | -24.15 Mn |
| Jun 30, 2023 | -16.01 Mn |
| Mar 31, 2023 | -28.08 Mn |
| Dec 31, 2022 | 10.23 Mn |
| Sep 30, 2022 | 31.66 Mn |
| Jun 30, 2022 | -1.40 Mn |
| Mar 31, 2022 | -2.91 Mn |
| Dec 31, 2021 | 18.04 Mn |
| Sep 30, 2021 | 11.92 Mn |
Datadog Change in Accured Expenses 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=change-in-accured-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();