Opera (OPRA) Non-Current Assets (2016 - 2026)
Opera's Non-Current Assets was $881.16 million in Q2 2026, up 6.6% from $826.68 million a year earlier and up 0.4% from the prior quarter.
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Analysis
Opera (OPRA) Non-Current Assets (2016 - 2026) Analysis & Trends
At the end of FY2025, Non-Current Assets at Opera came in at $863.79 million, up 4.9% from FY2024.
- Non-Current Assets has now increased for four consecutive years, though with a five-year compound annual growth rate of -1.4% (FY2020 to FY2025).
- In earlier years, Non-Current Assets was $823.68 million in FY2024 (+2.6%), $802.48 million in FY2023 (+28.5%), $624.47 million in FY2022 (+13.2%) and $551.48 million in FY2021 (-40.4%).
- The Q2 2026 figure marks the highest quarterly Non-Current Assets since Q3 2021.
- Compared with a year earlier, Non-Current Assets has increased for 11 straight quarters, with growth averaging 9.0% over the last eight quarters.
- The best year-over-year quarter for Non-Current Assets over five years was Q3 2024 (growth of 50.0%); the worst was Q4 2021 (a decline of 40.4%).
- Per Business Quant data, OPRA's Non-Current Assets in the three quarters before Q2 2026 was $877.85 million (Q1 2026), $863.79 million (Q4 2025) and $826.57 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.94 Bn | 241.02 Bn | 2.30 Bn | 39.82 Bn |
| 2 | CrowdStrike Holdings | 232.94 Bn | 213.35 Bn | 1.10 Bn | 5.07 Bn |
| 3 | Fortinet | 124.91 Bn | 110.84 Bn | 1.64 Bn | 4.65 Bn |
| 4 | Snowflake | 112.07 Bn | 99.38 Bn | 1.04 Bn | 5.20 Bn |
| 5 | Datadog | 91.70 Bn | 73.34 Bn | 881.34 Mn | 1.54 Bn |
| 6 | Zscaler | 34.52 Bn | 20.64 Bn | - | 2.84 Bn |
| 7 | Okta | 33.89 Bn | 23.98 Bn | 641.00 Mn | 6.05 Bn |
| 8 | Axon Enterprise | 32.10 Bn | 26.62 Bn | 546.45 Mn | 4.48 Bn |
| 9 | MongoDB | 29.30 Bn | 19.76 Bn | 569.77 Mn | 651.70 Mn |
| 10 | Opera | 1.58 Bn | 858.55 Mn | 114.91 Mn | 881.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 881.16 Mn |
| Mar 31, 2026 | 877.85 Mn |
| Dec 31, 2025 | 863.79 Mn |
| Sep 30, 2025 | 826.57 Mn |
| Jun 30, 2025 | 826.68 Mn |
| Mar 31, 2025 | 824.52 Mn |
| Dec 31, 2024 | 823.68 Mn |
| Sep 30, 2024 | 819.24 Mn |
| Jun 30, 2024 | 821.22 Mn |
| Mar 31, 2024 | 822.79 Mn |
| Dec 31, 2023 | 802.48 Mn |
| Sep 30, 2023 | 546.08 Mn |
| Jun 30, 2023 | 554.00 Mn |
| Mar 31, 2023 | 573.77 Mn |
| Dec 31, 2022 | 624.47 Mn |
| Sep 30, 2022 | 684.41 Mn |
| Jun 30, 2022 | 648.67 Mn |
| Mar 31, 2022 | 607.75 Mn |
| Dec 31, 2021 | 551.48 Mn |
| Sep 30, 2021 | 958.11 Mn |
API Access
Opera Non-Current Assets 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=non-current-assets&ticker=OPRA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-assets", "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=non-current-assets&ticker=OPRA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();