AvePoint (AVPT) Total Current Liabilities (2019 - 2026)
AvePoint (AVPT) recorded Total Current Liabilities of $278.93 million in Q2 2026, up 22.2% from $228.23 million a year earlier and up 7.2% from the prior quarter.
AvePoint (AVPT) Total Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, AvePoint reported Total Current Liabilities of $273.69 million, up 22.8% from FY2024.
- Annual Total Current Liabilities has increased for five straight years, with a five-year compound annual growth rate of 24.3% (FY2020 to FY2025).
- Across earlier years, Total Current Liabilities came in at $222.96 million in FY2024 (+26.2%), $176.67 million in FY2023 (+23.8%), $142.71 million in FY2022 (+28.4%) and $111.18 million in FY2021 (+20.6%).
- The Q2 2026 figure is the highest quarterly Total Current Liabilities in data going back to Q3 2019.
- On a year-over-year basis, Total Current Liabilities has increased for 17 consecutive quarters, with growth averaging 26.5% over the last eight quarters.
- Over the past five years, the year-over-year growth in Total Current Liabilities ranged from 20.0% (Q3 2022) to 943.6% (Q2 2022).
- Per Business Quant, the preceding three quarters came in at $260.26 million (Q1 2026), $273.69 million (Q4 2025) and $244.86 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 9.92 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 4.43 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 4.84 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 3.72 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 1.87 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 1.40 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.03 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 2.96 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 13.13 Bn |
| 10 | AvePoint | 2.89 Bn | 1.08 Bn | 91.01 Mn | 278.93 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 278.93 Mn |
| Mar 31, 2026 | 260.26 Mn |
| Dec 31, 2025 | 273.69 Mn |
| Sep 30, 2025 | 244.86 Mn |
| Jun 30, 2025 | 228.23 Mn |
| Mar 31, 2025 | 208.21 Mn |
| Dec 31, 2024 | 222.96 Mn |
| Sep 30, 2024 | 194.70 Mn |
| Jun 30, 2024 | 172.73 Mn |
| Mar 31, 2024 | 163.46 Mn |
| Dec 31, 2023 | 176.67 Mn |
| Sep 30, 2023 | 148.83 Mn |
| Jun 30, 2023 | 139.24 Mn |
| Mar 31, 2023 | 127.99 Mn |
| Dec 31, 2022 | 142.71 Mn |
| Sep 30, 2022 | 119.19 Mn |
| Jun 30, 2022 | 108.63 Mn |
| Mar 31, 2022 | 105.15 Mn |
| Dec 31, 2021 | 111.18 Mn |
| Sep 30, 2021 | 99.30 Mn |
AvePoint Total Current 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-current-liabilities&ticker=AVPT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-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-current-liabilities&ticker=AVPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();