Datadog (DDOG) Interest Expenses (2020 - 2026)
Datadog (DDOG) posted Interest Expenses of $3.26 million for Q2 2026, up 5.9% from $3.08 million a year earlier and up 4.4% from the prior quarter.
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Analysis
Datadog (DDOG) Interest Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Interest Expenses at Datadog was $11.4 million, up 11.1% year-over-year; for FY2025, it was $11.06 million, up 56.5% from FY2024.
- Annual Interest Expenses shows a five-year compound annual growth rate of -18.3% (FY2020 to FY2025).
- In prior years, Datadog's Interest Expenses was $7.07 million in FY2024 (+12.2%), $6.3 million in FY2023 (-61.9%), $16.54 million in FY2022 (-21.5%) and $21.05 million in FY2021 (-30.8%).
- The Q2 2026 figure stands as the highest quarterly Interest Expenses since Q3 2022.
- On a year-over-year basis, Interest Expenses increased in seven of the last eight quarters, with growth averaging 51.6%.
- The strongest year-over-year quarter for Interest Expenses in the past five years was Q1 2025, with growth of 115.6%; the weakest was Q2 2023, with a decline of 66.4%.
- According to Business Quant data, Interest Expenses for the three prior quarters was $3.12 million (Q1 2026), $2.6 million (Q4 2025) and $2.42 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | - |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 6.05 Mn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 3.20 Mn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 2.08 Mn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 3.26 Mn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 28.10 Mn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 924,000.00 |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | -19.00 Mn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | - |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | -89.29 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.26 Mn |
| Mar 31, 2026 | 3.12 Mn |
| Dec 31, 2025 | 2.60 Mn |
| Sep 30, 2025 | 2.42 Mn |
| Jun 30, 2025 | 3.08 Mn |
| Mar 31, 2025 | 2.96 Mn |
| Dec 31, 2024 | 2.64 Mn |
| Sep 30, 2024 | 1.57 Mn |
| Jun 30, 2024 | 1.48 Mn |
| Mar 31, 2024 | 1.37 Mn |
| Dec 31, 2023 | 1.29 Mn |
| Sep 30, 2023 | 1.30 Mn |
| Jun 30, 2023 | 1.53 Mn |
| Mar 31, 2023 | 2.18 Mn |
| Dec 31, 2022 | 3.02 Mn |
| Sep 30, 2022 | 3.73 Mn |
| Jun 30, 2022 | 4.54 Mn |
| Mar 31, 2022 | 5.25 Mn |
| Dec 31, 2021 | 5.60 Mn |
| Sep 30, 2021 | 4.91 Mn |
API Access
Datadog Interest 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=interest-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-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=interest-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();