Datadog (DDOG) Total Liabilities (2018 - 2026)
Datadog (DDOG) posted Total Liabilities of $3.18 billion for Q2 2026, up 21.1% from $2.63 billion a year earlier and up 7.3% from the prior quarter.
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Analysis
Datadog (DDOG) Total Liabilities (2018 - 2026) Analysis & Trends
At the end of FY2025, Datadog's Total Liabilities came in at $2.91 billion, down 5.2% from FY2024.
- Annual Total Liabilities shows a five-year compound annual growth rate of 25.6% (FY2020 to FY2025).
- In prior years, Datadog's Total Liabilities was $3.07 billion in FY2024 (+60.7%), $1.91 billion in FY2023 (+19.8%), $1.59 billion in FY2022 (+19.0%) and $1.34 billion in FY2021 (+43.6%).
- The Q2 2026 figure stands as the highest quarterly Total Liabilities in data going back to Q4 2018.
- On a year-over-year basis, Total Liabilities increased in six of the last eight quarters, with growth averaging 26.1%.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q4 2024, with growth of 60.7%; the weakest was Q4 2025, with a decline of 5.2%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $2.96 billion (Q1 2026), $2.91 billion (Q4 2025) and $2.61 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 3.81 Bn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 797.71 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | 2.17 Bn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | 5.27 Bn |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | 27.69 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.18 Bn |
| Mar 31, 2026 | 2.96 Bn |
| Dec 31, 2025 | 2.91 Bn |
| Sep 30, 2025 | 2.61 Bn |
| Jun 30, 2025 | 2.63 Bn |
| Mar 31, 2025 | 3.09 Bn |
| Dec 31, 2024 | 3.07 Bn |
| Sep 30, 2024 | 2.00 Bn |
| Jun 30, 2024 | 2.01 Bn |
| Mar 31, 2024 | 1.94 Bn |
| Dec 31, 2023 | 1.91 Bn |
| Sep 30, 2023 | 1.74 Bn |
| Jun 30, 2023 | 1.66 Bn |
| Mar 31, 2023 | 1.63 Bn |
| Dec 31, 2022 | 1.59 Bn |
| Sep 30, 2022 | 1.51 Bn |
| Jun 30, 2022 | 1.44 Bn |
| Mar 31, 2022 | 1.41 Bn |
| Dec 31, 2021 | 1.34 Bn |
| Sep 30, 2021 | 1.24 Bn |
API Access
Datadog Total Liabilities 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=total-liabilities&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();