Datadog (DDOG) Non Operating Interest Expenses (2020 - 2026)
Datadog (DDOG) recorded Non Operating Interest Expenses of $3.24 million in Q3 2026, up 33.6% from $2.42 million a year earlier but down 0.6% from the prior quarter.
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Analysis
Datadog (DDOG) Non Operating Interest Expenses (2020 - 2026) Analysis & Trends
On a TTM basis, Datadog's Non Operating Interest Expenses came in at $12.21 million as of Sep 30, 2026, up 10.0% year-over-year; for FY2025, it was $11.06 million, up 56.5% from FY2024.
- Annual Non Operating Interest Expenses has a five-year compound annual growth rate of -18.3% (FY2020 to FY2025).
- Across earlier years, Non Operating Interest Expenses came in at $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%).
- Quarterly Non Operating Interest Expenses has ranged from $1.29 million in Q4 2023 to $5.6 million in Q4 2021 over the past five years.
- On a year-over-year basis, Non Operating Interest Expenses has increased for three consecutive quarters, with growth averaging 53.2% over the last eight quarters.
- Peak year-over-year performance for Non Operating Interest Expenses in the last five years was growth of 115.6% in Q1 2025, against a decline of 66.4% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $3.26 million (Q2 2026), $3.12 million (Q1 2026) and $2.6 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn | - |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn | 6.05 Mn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn | 2.08 Mn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn | 3.00 Mn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn | 3.24 Mn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn | 2.75 Mn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn | -19.00 Mn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn | 28.10 Mn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn | 924,000.00 |
| 10 | Roku | 23.89 Bn | 13.92 Bn | 648.52 Mn | 593,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.24 Mn |
| 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 |
API Access
Datadog Non Operating 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=non-operating-interest-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-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=non-operating-interest-expenses&ticker=DDOG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();