JFrog (FROG) Total Liabilities (2019 - 2026)
JFrog (FROG) recorded Total Liabilities of $528.64 million in Q2 2026, up 38.5% from $381.73 million a year earlier and up 17.7% from the prior quarter.
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Analysis
JFrog (FROG) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, JFrog reported Total Liabilities of $453.93 million, up 27.4% from FY2024.
- Annual Total Liabilities has increased for five straight years, with a five-year compound annual growth rate of 27.4% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $356.38 million in FY2024 (+21.5%), $293.43 million in FY2023 (+19.1%), $246.45 million in FY2022 (+15.2%) and $213.95 million in FY2021 (+58.1%).
- The Q2 2026 figure is the highest quarterly Total Liabilities in data going back to Q4 2019.
- On a year-over-year basis, Total Liabilities has increased for 20 consecutive quarters, with growth averaging 26.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Liabilities ran from 11.6% in Q2 2023 to 72.4% in Q3 2021.
- Per Business Quant, the preceding three quarters came in at $449.21 million (Q1 2026), $453.93 million (Q4 2025) and $406.11 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 | JFrog | 10.93 Bn | 8.01 Bn | 127.62 Mn | 528.64 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 528.64 Mn |
| Mar 31, 2026 | 449.21 Mn |
| Dec 31, 2025 | 453.93 Mn |
| Sep 30, 2025 | 406.11 Mn |
| Jun 30, 2025 | 381.73 Mn |
| Mar 31, 2025 | 356.19 Mn |
| Dec 31, 2024 | 356.38 Mn |
| Sep 30, 2024 | 324.68 Mn |
| Jun 30, 2024 | 299.71 Mn |
| Mar 31, 2024 | 289.28 Mn |
| Dec 31, 2023 | 293.43 Mn |
| Sep 30, 2023 | 266.51 Mn |
| Jun 30, 2023 | 259.23 Mn |
| Mar 31, 2023 | 249.81 Mn |
| Dec 31, 2022 | 246.45 Mn |
| Sep 30, 2022 | 227.71 Mn |
| Jun 30, 2022 | 232.25 Mn |
| Mar 31, 2022 | 219.88 Mn |
| Dec 31, 2021 | 213.95 Mn |
| Sep 30, 2021 | 185.44 Mn |
API Access
JFrog 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=FROG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "FROG", "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=FROG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();