Red Violet (RDVT) Operating Expenses (2017 - 2026)
Red Violet (RDVT) reported Operating Expenses of $20.62 million for Q2 2026, up 8.4% from $19.02 million a year earlier and up 1.2% from the prior quarter.
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Analysis
Red Violet (RDVT) Operating Expenses (2017 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Red Violet's Operating Expenses came in at $81.31 million, up 12.0% year-over-year; for FY2025, it was $77.11 million, up 14.6% from FY2024.
- Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 13.2% (FY2020 to FY2025).
- By year, Operating Expenses came in at $67.27 million in FY2024 (+16.6%), $57.7 million in FY2023 (+9.0%), $52.96 million in FY2022 (+16.8%) and $45.34 million in FY2021 (+9.5%).
- Five-year quarterly Operating Expenses spans a low of $10.41 million in Q3 2021 and a high of $21.79 million in Q4 2025.
- Year over year, Operating Expenses has now increased in each of the last 21 quarters, with growth averaging 15.0% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 2.2% in Q3 2021 to 23.6% in Q3 2022.
- Per Business Quant data, the three quarters before Q2 2026 came in at $20.39 million (Q1 2026), $21.79 million (Q4 2025) and $18.51 million (Q3 2025).
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 | Red Violet | 1.11 Bn | 927.20 Mn | 22.90 Mn | 20.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 20.62 Mn |
| Mar 31, 2026 | 20.39 Mn |
| Dec 31, 2025 | 21.79 Mn |
| Sep 30, 2025 | 18.51 Mn |
| Jun 30, 2025 | 19.02 Mn |
| Mar 31, 2025 | 17.79 Mn |
| Dec 31, 2024 | 19.19 Mn |
| Sep 30, 2024 | 16.56 Mn |
| Jun 30, 2024 | 15.99 Mn |
| Mar 31, 2024 | 15.53 Mn |
| Dec 31, 2023 | 15.96 Mn |
| Sep 30, 2023 | 14.07 Mn |
| Jun 30, 2023 | 13.45 Mn |
| Mar 31, 2023 | 14.23 Mn |
| Dec 31, 2022 | 14.99 Mn |
| Sep 30, 2022 | 12.87 Mn |
| Jun 30, 2022 | 12.66 Mn |
| Mar 31, 2022 | 12.45 Mn |
| Dec 31, 2021 | 12.85 Mn |
| Sep 30, 2021 | 10.41 Mn |
API Access
Red Violet 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=RDVT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RDVT", "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=RDVT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();