N-able (NABL) Total Non-Current Liabilities (2020 - 2026)
N-able's Total Non-Current Liabilities came in at $590.15 million for Q2 2026, up 2.2% from $577.22 million a year earlier but down 1.3% from the prior quarter.
N-able (NABL) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, N-able's Total Non-Current Liabilities was $606.99 million, up 6.4% from FY2024.
- Total Non-Current Liabilities has increased in each of the last three years, with a five-year compound annual growth rate of 6.3% (FY2020 to FY2025).
- Going back by year, Total Non-Current Liabilities was $570.25 million in FY2024 (+27.4%), $447.71 million in FY2023 (+3.8%), $431.42 million in FY2022 (-1.3%) and $436.93 million in FY2021 (-2.5%).
- The five-year range for quarterly Total Non-Current Liabilities is $430.84 million (Q1 2023) to $606.99 million (Q4 2025).
- Year-over-year, Total Non-Current Liabilities has increased for 13 consecutive quarters, with growth averaging 16.3% over the last eight quarters.
- The fastest year-over-year change in Total Non-Current Liabilities over five years came in Q1 2025 (growth of 31.5%), and the weakest in Q3 2022 (a decline of 2.5%).
- Business Quant data shows NABL's Total Non-Current Liabilities at $598 million (Q1 2026), $606.99 million (Q4 2025) and $583.79 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 316.55 Bn | 301.63 Bn | 2.30 Bn | 19.68 Bn |
| 2 | CrowdStrike Holdings | 269.03 Bn | 249.47 Bn | 1.10 Bn | 6.57 Bn |
| 3 | Fortinet | 129.08 Bn | 115.01 Bn | 1.64 Bn | 9.17 Bn |
| 4 | Snowflake | 116.42 Bn | 103.73 Bn | 1.04 Bn | 6.45 Bn |
| 5 | Datadog | 96.40 Bn | 78.04 Bn | 881.34 Mn | 3.16 Bn |
| 6 | Okta | 34.24 Bn | 24.34 Bn | 641.00 Mn | 2.11 Bn |
| 7 | Axon Enterprise | 34.08 Bn | 28.61 Bn | 546.45 Mn | 3.68 Bn |
| 8 | Zscaler | 32.34 Bn | 18.46 Bn | - | 5.20 Bn |
| 9 | Baidu | 29.50 Bn | -44.13 Bn | 1.47 Mn | 12.63 Bn |
| 10 | N-able | 793.40 Mn | 346.51 Mn | 106.20 Mn | 590.15 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 590.15 Mn |
| Mar 31, 2026 | 598.00 Mn |
| Dec 31, 2025 | 606.99 Mn |
| Sep 30, 2025 | 583.79 Mn |
| Jun 30, 2025 | 577.22 Mn |
| Mar 31, 2025 | 576.36 Mn |
| Dec 31, 2024 | 570.25 Mn |
| Sep 30, 2024 | 458.17 Mn |
| Jun 30, 2024 | 447.69 Mn |
| Mar 31, 2024 | 438.34 Mn |
| Dec 31, 2023 | 447.71 Mn |
| Sep 30, 2023 | 444.60 Mn |
| Jun 30, 2023 | 438.92 Mn |
| Mar 31, 2023 | 430.84 Mn |
| Dec 31, 2022 | 431.42 Mn |
| Sep 30, 2022 | 433.02 Mn |
| Jun 30, 2022 | 432.37 Mn |
| Mar 31, 2022 | 431.19 Mn |
| Dec 31, 2021 | 436.93 Mn |
| Sep 30, 2021 | 444.25 Mn |
N-able 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=NABL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "NABL", "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=NABL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();