Qualys (QLYS) Total Liabilities (2011 - 2026)
Qualys (QLYS) posted Total Liabilities of $511.95 million for Q2 2026, up 4.2% from $491.34 million a year earlier but down 2.4% from the prior quarter.
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Analysis
Qualys (QLYS) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Qualys' Total Liabilities came in at $533.93 million, up 7.6% from FY2024.
- Annual Total Liabilities has increased for 13 consecutive years, with a five-year compound annual growth rate of 9.9% (FY2020 to FY2025).
- In prior years, Qualys' Total Liabilities was $496.42 million in FY2024 (+11.7%), $444.44 million in FY2023 (+7.9%), $411.81 million in FY2022 (+9.0%) and $377.85 million in FY2021 (+13.7%).
- Quarterly Total Liabilities has run from a low of $353.19 million in Q3 2021 to a high of $533.93 million in Q4 2025 over five years.
- On a year-over-year basis, Total Liabilities has increased in each of the last 51 quarters, with growth averaging 8.0% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Liabilities ran from 3.8% in Q2 2024 to 16.5% in Q1 2022.
- According to Business Quant data, Total Liabilities for the three prior quarters was $524.76 million (Q1 2026), $533.93 million (Q4 2025) and $502.59 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 | Qualys | 6.02 Bn | 4.26 Bn | 151.93 Mn | 511.95 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 511.95 Mn |
| Mar 31, 2026 | 524.76 Mn |
| Dec 31, 2025 | 533.93 Mn |
| Sep 30, 2025 | 502.59 Mn |
| Jun 30, 2025 | 491.34 Mn |
| Mar 31, 2025 | 498.44 Mn |
| Dec 31, 2024 | 496.42 Mn |
| Sep 30, 2024 | 458.73 Mn |
| Jun 30, 2024 | 448.81 Mn |
| Mar 31, 2024 | 457.58 Mn |
| Dec 31, 2023 | 444.44 Mn |
| Sep 30, 2023 | 428.94 Mn |
| Jun 30, 2023 | 432.57 Mn |
| Mar 31, 2023 | 407.93 Mn |
| Dec 31, 2022 | 411.81 Mn |
| Sep 30, 2022 | 392.45 Mn |
| Jun 30, 2022 | 392.17 Mn |
| Mar 31, 2022 | 387.92 Mn |
| Dec 31, 2021 | 377.85 Mn |
| Sep 30, 2021 | 353.19 Mn |
API Access
Qualys 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=QLYS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "QLYS", "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=QLYS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();