AvePoint (AVPT) Operating Expenses (2019 - 2026)
AvePoint (AVPT) recorded Operating Expenses of $80.78 million in Q2 2026, up 18.0% from $68.45 million a year earlier and up 11.2% from the prior quarter.
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Analysis
AvePoint (AVPT) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, AvePoint's Operating Expenses came in at $296.76 million as of Jun 30, 2026, up 15.6% year-over-year; for FY2025, it was $277.66 million, up 15.3% from FY2024.
- Annual Operating Expenses has increased for six straight years, with a five-year compound annual growth rate of 17.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $240.79 million in FY2024 (+14.8%), $209.72 million in FY2023 (+1.2%), $207.13 million in FY2022 (+7.7%) and $192.4 million in FY2021 (+51.9%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q2 2019.
- On a year-over-year basis, Operating Expenses has increased for 11 consecutive quarters, with growth averaging 14.8% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 89.5% in Q3 2021, against a decline of 21.3% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $72.64 million (Q1 2026), $69.88 million (Q4 2025) and $73.45 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 | AvePoint | 2.89 Bn | 1.08 Bn | 91.01 Mn | 80.78 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.78 Mn |
| Mar 31, 2026 | 72.64 Mn |
| Dec 31, 2025 | 69.88 Mn |
| Sep 30, 2025 | 73.45 Mn |
| Jun 30, 2025 | 68.45 Mn |
| Mar 31, 2025 | 65.88 Mn |
| Dec 31, 2024 | 62.41 Mn |
| Sep 30, 2024 | 59.93 Mn |
| Jun 30, 2024 | 61.16 Mn |
| Mar 31, 2024 | 57.29 Mn |
| Dec 31, 2023 | 54.13 Mn |
| Sep 30, 2023 | 52.92 Mn |
| Jun 30, 2023 | 52.16 Mn |
| Mar 31, 2023 | 50.51 Mn |
| Dec 31, 2022 | 52.87 Mn |
| Sep 30, 2022 | 53.07 Mn |
| Jun 30, 2022 | 51.83 Mn |
| Mar 31, 2022 | 49.36 Mn |
| Dec 31, 2021 | 46.23 Mn |
| Sep 30, 2021 | 67.39 Mn |
API Access
AvePoint 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=AVPT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AVPT", "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=AVPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();