Datadog (DDOG) Total Current Liabilities (2018 - 2026)
Datadog's Total Current Liabilities came in at $1.87 billion for Q2 2026, up 38.6% from $1.35 billion a year earlier and up 13.2% from the prior quarter.
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Analysis
Datadog (DDOG) Total Current Liabilities (2018 - 2026) Analysis & Trends
At the end of FY2025, Datadog's Total Current Liabilities was $1.59 billion, down 14.6% from FY2024.
- Total Current Liabilities carries a five-year compound annual growth rate of 39.8% (FY2020 to FY2025).
- Going back by year, Total Current Liabilities was $1.86 billion in FY2024 (+85.7%), $1 billion in FY2023 (+32.0%), $759.75 million in FY2022 (+43.7%) and $528.7 million in FY2021 (+77.5%).
- The Q2 2026 figure represents the highest quarterly Total Current Liabilities in data going back to Q4 2018.
- Year-over-year, Total Current Liabilities increased in four of the last eight quarters, with growth averaging 31.3%.
- The fastest year-over-year change in Total Current Liabilities over five years came in Q2 2024 (growth of 135.2%), and the weakest in Q3 2025 (a decline of 25.8%).
- Business Quant data shows DDOG's Total Current Liabilities at $1.66 billion (Q1 2026), $1.59 billion (Q4 2025) and $1.32 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 9.92 Bn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 4.43 Bn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 4.84 Bn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 3.72 Bn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 1.87 Bn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 1.40 Bn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 642.37 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | 2.03 Bn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | 2.96 Bn |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | 13.13 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.87 Bn |
| Mar 31, 2026 | 1.66 Bn |
| Dec 31, 2025 | 1.59 Bn |
| Sep 30, 2025 | 1.32 Bn |
| Jun 30, 2025 | 1.35 Bn |
| Mar 31, 2025 | 1.85 Bn |
| Dec 31, 2024 | 1.86 Bn |
| Sep 30, 2024 | 1.78 Bn |
| Jun 30, 2024 | 1.79 Bn |
| Mar 31, 2024 | 972.79 Mn |
| Dec 31, 2023 | 1.00 Bn |
| Sep 30, 2023 | 842.48 Mn |
| Jun 30, 2023 | 761.36 Mn |
| Mar 31, 2023 | 772.95 Mn |
| Dec 31, 2022 | 759.75 Mn |
| Sep 30, 2022 | 674.41 Mn |
| Jun 30, 2022 | 625.88 Mn |
| Mar 31, 2022 | 601.97 Mn |
| Dec 31, 2021 | 528.70 Mn |
| Sep 30, 2021 | 440.20 Mn |
API Access
Datadog Total Current 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-current-liabilities&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-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-current-liabilities&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();