Opera (OPRA) Total Non-Current Liabilities (2016 - 2026)
Opera (OPRA) recorded Total Non-Current Liabilities of $11.54 million in Q2 2026, down 16.1% from $13.75 million a year earlier and down 1.9% from the prior quarter.
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Analysis
Opera (OPRA) Total Non-Current Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Opera reported Total Non-Current Liabilities of $13.77 million, down 4.3% from FY2024.
- Annual Total Non-Current Liabilities has a five-year compound annual growth rate of -2.2% (FY2020 to FY2025).
- Across earlier years, Total Non-Current Liabilities came in at $14.39 million in FY2024 (+48.6%), $9.68 million in FY2023 (-20.3%), $12.14 million in FY2022 (+40.6%) and $8.64 million in FY2021 (-43.9%).
- Quarterly Total Non-Current Liabilities has ranged from $5.89 million in Q3 2023 to $14.39 million in Q4 2024 over the past five years.
- On a year-over-year basis, Total Non-Current Liabilities has declined for three consecutive quarters, with growth averaging 15.2% over the last eight quarters.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 65.1% in Q1 2023, against a decline of 52.0% in Q1 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $11.76 million (Q1 2026), $13.77 million (Q4 2025) and $10.97 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 260.12 Bn | 245.19 Bn | 2.30 Bn | 19.68 Bn |
| 2 | CrowdStrike Holdings | 232.49 Bn | 212.89 Bn | 1.10 Bn | 6.57 Bn |
| 3 | Fortinet | 125.70 Bn | 111.63 Bn | 1.64 Bn | 9.17 Bn |
| 4 | Snowflake | 110.19 Bn | 97.50 Bn | 1.04 Bn | 6.45 Bn |
| 5 | Datadog | 92.71 Bn | 74.35 Bn | 881.34 Mn | 3.16 Bn |
| 6 | Zscaler | 34.07 Bn | 20.19 Bn | - | 5.20 Bn |
| 7 | Okta | 33.06 Bn | 23.16 Bn | 641.00 Mn | 2.11 Bn |
| 8 | Axon Enterprise | 30.90 Bn | 25.43 Bn | 546.45 Mn | 3.62 Bn |
| 9 | MongoDB | 28.04 Bn | 18.51 Bn | 569.77 Mn | 770.18 Mn |
| 10 | Opera | 1.58 Bn | 857.21 Mn | 114.91 Mn | 11.54 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 11.54 Mn |
| Mar 31, 2026 | 11.76 Mn |
| Dec 31, 2025 | 13.77 Mn |
| Sep 30, 2025 | 10.97 Mn |
| Jun 30, 2025 | 13.75 Mn |
| Mar 31, 2025 | 12.59 Mn |
| Dec 31, 2024 | 14.39 Mn |
| Sep 30, 2024 | 9.05 Mn |
| Jun 30, 2024 | 11.11 Mn |
| Mar 31, 2024 | 12.40 Mn |
| Dec 31, 2023 | 9.68 Mn |
| Sep 30, 2023 | 5.89 Mn |
| Jun 30, 2023 | 9.54 Mn |
| Mar 31, 2023 | 12.62 Mn |
| Dec 31, 2022 | 12.14 Mn |
| Sep 30, 2022 | 9.56 Mn |
| Jun 30, 2022 | 8.71 Mn |
| Mar 31, 2022 | 7.65 Mn |
| Dec 31, 2021 | 8.64 Mn |
| Sep 30, 2021 | 12.87 Mn |
API Access
Opera 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=OPRA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "OPRA", "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=OPRA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();