Rapid7 (RPD) Accumulated Expenses (2014 - 2026)
Rapid7's Accumulated Expenses was $93.43 million in Q2 2026, up 19.6% from $78.13 million a year earlier and up 10.7% from the prior quarter.
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Analysis
Rapid7 (RPD) Accumulated Expenses (2014 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Rapid7 came in at $97 million, up 9.2% from FY2024.
- Accumulated Expenses has now increased for three consecutive years, with a five-year compound annual growth rate of 9.5% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $88.8 million in FY2024 (+4.4%), $85.03 million in FY2023 (+5.9%), $80.31 million in FY2022 (-2.8%) and $82.62 million in FY2021 (+34.0%).
- Quarterly Accumulated Expenses has moved between $56.5 million (Q1 2022) and $97 million (Q4 2025) over five years.
- Compared with a year earlier, Accumulated Expenses has increased for three straight quarters, with growth averaging 14.2% over the last eight quarters.
- The best year-over-year quarter for Accumulated Expenses over five years was Q4 2021 (growth of 34.0%); the worst was Q2 2024 (a decline of 3.2%).
- Per Business Quant data, RPD's Accumulated Expenses in the three quarters before Q2 2026 was $84.41 million (Q1 2026), $97 million (Q4 2025) and $80.54 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | Rapid7 | 822.60 Mn | -1.43 Bn | 145.34 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 93.43 Mn |
| Mar 31, 2026 | 84.41 Mn |
| Dec 31, 2025 | 97.00 Mn |
| Sep 30, 2025 | 80.54 Mn |
| Jun 30, 2025 | 78.13 Mn |
| Mar 31, 2025 | 69.46 Mn |
| Dec 31, 2024 | 88.80 Mn |
| Sep 30, 2024 | 82.32 Mn |
| Jun 30, 2024 | 67.24 Mn |
| Mar 31, 2024 | 60.61 Mn |
| Dec 31, 2023 | 85.03 Mn |
| Sep 30, 2023 | 63.39 Mn |
| Jun 30, 2023 | 69.46 Mn |
| Mar 31, 2023 | 57.55 Mn |
| Dec 31, 2022 | 80.31 Mn |
| Sep 30, 2022 | 64.43 Mn |
| Jun 30, 2022 | 66.35 Mn |
| Mar 31, 2022 | 56.50 Mn |
| Dec 31, 2021 | 82.62 Mn |
| Sep 30, 2021 | 57.98 Mn |
API Access
Rapid7 Accumulated 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=accumulated-expenses&ticker=RPD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=RPD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();