Dynatrace (DT) Operating Expenses (2018 - 2026)
Dynatrace's Operating Expenses was $379.62 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 15.1% from $329.8 million a year earlier but down 3.4% from the prior quarter.
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Analysis
Dynatrace (DT) Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Dynatrace's Operating Expenses was $1.45 billion through Jun 30, 2026, up 16.4% year-over-year; for FY2026 (ended Mar 31, 2026), it was $1.4 billion, up 16.8% from FY2025.
- Operating Expenses has now increased for five consecutive fiscal years, with a five-year compound annual growth rate of 23.7% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $1.2 billion in FY2025 (+15.8%), $1.04 billion in FY2024 (+22.9%), $842.83 million in FY2023 (+24.8%) and $675.26 million in FY2022 (+39.5%).
- Quarterly Operating Expenses has moved between $163.44 million (fiscal Q2 2022) and $392.98 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for 23 straight quarters, with growth averaging 15.8% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 11.0% in fiscal Q4 2025 to 42.1% in fiscal Q2 2022.
- Per Business Quant data, DT's Operating Expenses in the three fiscal quarters before Q1 2027 was $392.98 million (Q4 2026), $346.9 million (Q3 2026) and $331.12 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 499.67 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Dynatrace | 16.79 Bn | 12.01 Bn | 451.10 Mn | 379.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 379.62 Mn |
| Mar 31, 2026 | 392.98 Mn |
| Dec 31, 2025 | 346.90 Mn |
| Sep 30, 2025 | 331.12 Mn |
| Jun 30, 2025 | 329.80 Mn |
| Mar 31, 2025 | 317.16 Mn |
| Dec 31, 2024 | 306.14 Mn |
| Sep 30, 2024 | 293.32 Mn |
| Jun 30, 2024 | 282.44 Mn |
| Mar 31, 2024 | 285.85 Mn |
| Dec 31, 2023 | 261.51 Mn |
| Sep 30, 2023 | 252.06 Mn |
| Jun 30, 2023 | 236.25 Mn |
| Mar 31, 2023 | 235.48 Mn |
| Dec 31, 2022 | 207.75 Mn |
| Sep 30, 2022 | 203.22 Mn |
| Jun 30, 2022 | 196.38 Mn |
| Mar 31, 2022 | 187.04 Mn |
| Dec 31, 2021 | 175.09 Mn |
| Sep 30, 2021 | 163.44 Mn |
API Access
Dynatrace Operating 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=operating-expenses&ticker=DT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=DT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();