Bentley Systems (BSY) Operating Expenses (2019 - 2026)
Bentley Systems' Operating Expenses came in at $248.13 million for Q2 2026, up 17.7% from $210.9 million a year earlier and up 10.7% from the prior quarter.
Bentley Systems (BSY) Operating Expenses (2019 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Bentley Systems reported Operating Expenses of $933.31 million, up 13.4% year-over-year; for FY2025, it came in at $861.63 million, up 8.6% from FY2024.
- Operating Expenses has increased in each of the last three years, with a five-year compound annual growth rate of 12.2% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $793.18 million in FY2024 (+8.4%), $731.79 million in FY2023 (+12.0%), $653.46 million in FY2022 (-0.1%) and $653.92 million in FY2021 (+35.0%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q3 2019.
- Year-over-year, Operating Expenses has increased for 15 consecutive quarters, with growth averaging 12.2% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 51.4%), and the weakest in Q3 2022 (a decline of 34.6%).
- Business Quant data shows BSY's Operating Expenses at $224.15 million (Q1 2026), $242.17 million (Q4 2025) and $218.86 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 50.52 Bn | 22.77 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 24.02 Bn | 20.79 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Ptc | 22.16 Bn | 20.98 Bn | 490.47 Mn | 323.96 Mn |
| 5 | Toast | 18.74 Bn | 11.41 Bn | 516.00 Mn | 364.00 Mn |
| 6 | Trimble | 14.17 Bn | 13.23 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Manhattan Associates | 13.17 Bn | 12.17 Bn | 168.33 Mn | 231.56 Mn |
| 8 | Costar | 12.94 Bn | 6.89 Bn | 728.00 Mn | 652.00 Mn |
| 9 | Bentley Systems | 11.23 Bn | 10.69 Bn | 336.74 Mn | 248.13 Mn |
| 10 | Procore Technologies | 8.77 Bn | 6.07 Bn | 299.80 Mn | 295.47 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 248.13 Mn |
| Mar 31, 2026 | 224.15 Mn |
| Dec 31, 2025 | 242.17 Mn |
| Sep 30, 2025 | 218.86 Mn |
| Jun 30, 2025 | 210.90 Mn |
| Mar 31, 2025 | 189.70 Mn |
| Dec 31, 2024 | 220.50 Mn |
| Sep 30, 2024 | 201.71 Mn |
| Jun 30, 2024 | 186.97 Mn |
| Mar 31, 2024 | 184.00 Mn |
| Dec 31, 2023 | 205.07 Mn |
| Sep 30, 2023 | 168.26 Mn |
| Jun 30, 2023 | 177.02 Mn |
| Mar 31, 2023 | 181.44 Mn |
| Dec 31, 2022 | 183.84 Mn |
| Sep 30, 2022 | 153.61 Mn |
| Jun 30, 2022 | 152.87 Mn |
| Mar 31, 2022 | 163.14 Mn |
| Dec 31, 2021 | 164.90 Mn |
| Sep 30, 2021 | 234.70 Mn |
Bentley Systems 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=BSY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BSY", "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=BSY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();