Rapid7 (RPD) Operating Expenses (2014 - 2026)
Rapid7's Operating Expenses came in at $142.32 million for Q2 2026, down 3.6% from $147.64 million a year earlier and down 2.2% from the prior quarter.
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Analysis
Rapid7 (RPD) Operating Expenses (2014 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Rapid7 reported Operating Expenses of $582.49 million, up 0.4% year-over-year; for FY2025, it was $593.19 million, up 6.3% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 10.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $557.94 million in FY2024 (-11.4%), $629.95 million in FY2023 (+8.2%), $582.35 million in FY2022 (+19.7%) and $486.52 million in FY2021 (+33.6%).
- The Q2 2026 figure represents the lowest quarterly Operating Expenses since Q3 2024.
- Year-over-year, Operating Expenses increased in five of the last eight quarters, with growth averaging 1.3%.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 42.3%), and the weakest in Q2 2024 (a decline of 22.9%).
- Business Quant data shows RPD's Operating Expenses at $145.5 million (Q1 2026), $147.6 million (Q4 2025) and $147.07 million (Q3 2025) in the three quarters before 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 | Rapid7 | 794.33 Mn | -1.46 Bn | 145.34 Mn | 142.32 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 142.32 Mn |
| Mar 31, 2026 | 145.50 Mn |
| Dec 31, 2025 | 147.60 Mn |
| Sep 30, 2025 | 147.07 Mn |
| Jun 30, 2025 | 147.64 Mn |
| Mar 31, 2025 | 150.87 Mn |
| Dec 31, 2024 | 143.09 Mn |
| Sep 30, 2024 | 138.68 Mn |
| Jun 30, 2024 | 141.78 Mn |
| Mar 31, 2024 | 134.39 Mn |
| Dec 31, 2023 | 137.84 Mn |
| Sep 30, 2023 | 157.05 Mn |
| Jun 30, 2023 | 183.92 Mn |
| Mar 31, 2023 | 151.14 Mn |
| Dec 31, 2022 | 142.89 Mn |
| Sep 30, 2022 | 145.15 Mn |
| Jun 30, 2022 | 147.83 Mn |
| Mar 31, 2022 | 146.47 Mn |
| Dec 31, 2021 | 142.47 Mn |
| Sep 30, 2021 | 130.74 Mn |
API Access
Rapid7 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=RPD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RPD", "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=RPD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();