Varonis Systems (VRNS) Operating Expenses (2013 - 2026)
Varonis Systems (VRNS) reported Operating Expenses of $176.14 million for Q2 2026, up 11.9% from $157.47 million a year earlier and up 0.1% from the prior quarter.
Varonis Systems (VRNS) Operating Expenses (2013 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Varonis Systems' Operating Expenses came in at $681.61 million, up 12.4% year-over-year; for FY2025, it came in at $638.07 million, up 11.0% from FY2024.
- Operating Expenses has increased for 13 consecutive years, with a five-year compound annual growth rate of 14.3% (FY2020 to FY2025).
- By year, Operating Expenses came in at $574.75 million in FY2024 (+5.5%), $544.63 million in FY2023 (+3.7%), $525.03 million in FY2022 (+22.3%) and $429.43 million in FY2021 (+31.4%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q1 2013.
- Year over year, Operating Expenses has now increased in each of the last eight quarters, with growth averaging 11.2% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 41.3%); the low point was Q2 2024 (a decline of 0.7%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $176.04 million (Q1 2026), $167.07 million (Q4 2025) and $162.36 million (Q3 2025).
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 | Varonis Systems | 5.50 Bn | 2.54 Bn | 135.51 Mn | 176.14 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 176.14 Mn |
| Mar 31, 2026 | 176.04 Mn |
| Dec 31, 2025 | 167.07 Mn |
| Sep 30, 2025 | 162.36 Mn |
| Jun 30, 2025 | 157.47 Mn |
| Mar 31, 2025 | 151.17 Mn |
| Dec 31, 2024 | 150.01 Mn |
| Sep 30, 2024 | 147.70 Mn |
| Jun 30, 2024 | 136.74 Mn |
| Mar 31, 2024 | 140.31 Mn |
| Dec 31, 2023 | 140.00 Mn |
| Sep 30, 2023 | 134.07 Mn |
| Jun 30, 2023 | 137.75 Mn |
| Mar 31, 2023 | 132.81 Mn |
| Dec 31, 2022 | 135.58 Mn |
| Sep 30, 2022 | 131.69 Mn |
| Jun 30, 2022 | 131.22 Mn |
| Mar 31, 2022 | 126.54 Mn |
| Dec 31, 2021 | 127.03 Mn |
| Sep 30, 2021 | 104.57 Mn |
Varonis 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=VRNS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "VRNS", "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=VRNS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();