AvePoint (AVPT) Total Liabilities (2019 - 2026)
AvePoint's Total Liabilities was $320.13 million in Q2 2026, up 24.6% from $256.99 million a year earlier and up 8.4% from the prior quarter.
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Analysis
AvePoint (AVPT) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at AvePoint came in at $310.48 million, up 25.1% from FY2024.
- Total Liabilities has now increased for four consecutive years, though with a five-year compound annual growth rate of -3.0% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $248.11 million in FY2024 (+10.9%), $223.78 million in FY2023 (+20.1%), $186.39 million in FY2022 (+34.7%) and $138.38 million in FY2021 (-61.8%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities since Q2 2021.
- Compared with a year earlier, Total Liabilities has increased for 16 straight quarters, with growth averaging 19.6% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2022 (growth of 34.7%); the worst was Q3 2021 (a decline of 74.7%).
- Per Business Quant data, AVPT's Total Liabilities in the three quarters before Q2 2026 was $295.38 million (Q1 2026), $310.48 million (Q4 2025) and $276.71 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 3.81 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.17 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 5.27 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 27.69 Bn |
| 10 | AvePoint | 2.89 Bn | 1.08 Bn | 91.01 Mn | 320.13 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 320.13 Mn |
| Mar 31, 2026 | 295.38 Mn |
| Dec 31, 2025 | 310.48 Mn |
| Sep 30, 2025 | 276.71 Mn |
| Jun 30, 2025 | 256.99 Mn |
| Mar 31, 2025 | 237.40 Mn |
| Dec 31, 2024 | 248.11 Mn |
| Sep 30, 2024 | 247.23 Mn |
| Jun 30, 2024 | 219.86 Mn |
| Mar 31, 2024 | 201.07 Mn |
| Dec 31, 2023 | 223.78 Mn |
| Sep 30, 2023 | 198.10 Mn |
| Jun 30, 2023 | 187.45 Mn |
| Mar 31, 2023 | 174.27 Mn |
| Dec 31, 2022 | 186.39 Mn |
| Sep 30, 2022 | 162.13 Mn |
| Jun 30, 2022 | 150.67 Mn |
| Mar 31, 2022 | 146.23 Mn |
| Dec 31, 2021 | 138.38 Mn |
| Sep 30, 2021 | 132.67 Mn |
API Access
AvePoint Total Liabilities 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=total-liabilities&ticker=AVPT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=AVPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();