JFrog (FROG) Total Non-Current Liabilities (2020 - 2026)
JFrog (FROG) posted Total Non-Current Liabilities of $521.04 million for Q2 2026, up 39.0% from $374.91 million a year earlier and up 18.0% from the prior quarter.
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Analysis
JFrog (FROG) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, JFrog's Total Non-Current Liabilities came in at $446.6 million, up 27.3% from FY2024.
- Annual Total Non-Current Liabilities has increased for five consecutive years, with a five-year compound annual growth rate of 27.3% (FY2020 to FY2025).
- In prior years, JFrog's Total Non-Current Liabilities was $350.76 million in FY2024 (+21.3%), $289.12 million in FY2023 (+18.8%), $243.39 million in FY2022 (+14.1%) and $213.24 million in FY2021 (+59.4%).
- The Q2 2026 figure stands as the highest quarterly Total Non-Current Liabilities in data going back to Q3 2020.
- On a year-over-year basis, Total Non-Current Liabilities has increased in each of the last 20 quarters, with growth averaging 26.3% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Non-Current Liabilities ran from 11.1% in Q2 2023 to 72.0% in Q3 2021.
- According to Business Quant data, Total Non-Current Liabilities for the three prior quarters was $441.73 million (Q1 2026), $446.6 million (Q4 2025) and $399.46 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 235.00 Bn | 220.07 Bn | 2.30 Bn | 19.68 Bn |
| 2 | CrowdStrike Holdings | 221.18 Bn | 201.58 Bn | 1.10 Bn | 6.57 Bn |
| 3 | Snowflake | 96.49 Bn | 83.81 Bn | 1.04 Bn | 6.45 Bn |
| 4 | Fortinet | 87.26 Bn | 71.51 Bn | 1.64 Bn | 9.56 Bn |
| 5 | Datadog | 64.27 Bn | 44.82 Bn | 959.92 Mn | 3.10 Bn |
| 6 | Zscaler | 31.67 Bn | 17.82 Bn | 689.22 Mn | 5.20 Bn |
| 7 | Okta | 29.42 Bn | 19.51 Bn | 641.00 Mn | 2.11 Bn |
| 8 | Axon Enterprise | 25.30 Bn | 19.82 Bn | 546.45 Mn | 3.62 Bn |
| 9 | MongoDB | 25.20 Bn | 15.67 Bn | 569.77 Mn | 770.18 Mn |
| 10 | JFrog | 12.34 Bn | 9.41 Bn | 127.62 Mn | 521.04 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 521.04 Mn |
| Mar 31, 2026 | 441.73 Mn |
| Dec 31, 2025 | 446.60 Mn |
| Sep 30, 2025 | 399.46 Mn |
| Jun 30, 2025 | 374.91 Mn |
| Mar 31, 2025 | 349.35 Mn |
| Dec 31, 2024 | 350.76 Mn |
| Sep 30, 2024 | 320.17 Mn |
| Jun 30, 2024 | 295.26 Mn |
| Mar 31, 2024 | 284.90 Mn |
| Dec 31, 2023 | 289.12 Mn |
| Sep 30, 2023 | 262.80 Mn |
| Jun 30, 2023 | 255.74 Mn |
| Mar 31, 2023 | 246.52 Mn |
| Dec 31, 2022 | 243.39 Mn |
| Sep 30, 2022 | 224.75 Mn |
| Jun 30, 2022 | 230.11 Mn |
| Mar 31, 2022 | 218.47 Mn |
| Dec 31, 2021 | 213.24 Mn |
| Sep 30, 2021 | 184.30 Mn |
API Access
JFrog Total Non-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-non-current-liabilities&ticker=FROG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-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-non-current-liabilities&ticker=FROG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();