Opera (OPRA) Property, Plant & Equipment (Net) (2016 - 2026)
Opera's Property, Plant & Equipment (Net) was $32.11 million in Q2 2026, down 5.4% from $33.95 million a year earlier and down 4.1% from the prior quarter.
Opera (OPRA) Property, Plant & Equipment (Net) (2016 - 2026) Analysis & Trends
At the end of FY2025, Property, Plant & Equipment (Net) at Opera came in at $32.74 million, down 3.9% from FY2024.
- Property, Plant & Equipment (Net) shows a five-year compound annual growth rate of 12.5% (FY2020 to FY2025).
- In earlier years, Property, Plant & Equipment (Net) was $34.06 million in FY2024 (+111.9%), $16.07 million in FY2023 (+9.9%), $14.62 million in FY2022 (+19.2%) and $12.26 million in FY2021 (-32.5%).
- The Q2 2026 figure marks the lowest quarterly Property, Plant & Equipment (Net) since Q4 2023.
- Compared with a year earlier, Property, Plant & Equipment (Net) was higher in three of the last eight quarters, with growth averaging 27.7%.
- The best year-over-year quarter for Property, Plant & Equipment (Net) over five years was Q1 2024 (growth of 179.0%); the worst was Q1 2022 (a decline of 34.1%).
- Per Business Quant data, OPRA's Property, Plant & Equipment (Net) in the three quarters before Q2 2026 was $33.48 million (Q1 2026), $32.74 million (Q4 2025) and $32.44 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 310.15 Bn | 295.22 Bn | 2.30 Bn | 523.00 Mn |
| 2 | CrowdStrike Holdings | 263.73 Bn | 244.17 Bn | 1.10 Bn | 1.17 Bn |
| 3 | Fortinet | 132.04 Bn | 117.97 Bn | 1.64 Bn | 1.70 Bn |
| 4 | Snowflake | 114.70 Bn | 102.02 Bn | 1.04 Bn | 207.98 Mn |
| 5 | Datadog | 96.79 Bn | 78.43 Bn | 881.34 Mn | 409.63 Mn |
| 6 | Zscaler | 41.60 Bn | 27.72 Bn | - | 753.00 Mn |
| 7 | Okta | 35.61 Bn | 25.70 Bn | 641.00 Mn | 33.00 Mn |
| 8 | Axon Enterprise | 34.15 Bn | 28.67 Bn | 546.45 Mn | 341.51 Mn |
| 9 | MongoDB | 29.89 Bn | 20.36 Bn | 569.77 Mn | 38.99 Mn |
| 10 | Opera | 1.56 Bn | 833.74 Mn | 114.91 Mn | 32.11 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 32.11 Mn |
| Mar 31, 2026 | 33.48 Mn |
| Dec 31, 2025 | 32.74 Mn |
| Sep 30, 2025 | 32.44 Mn |
| Jun 30, 2025 | 33.95 Mn |
| Mar 31, 2025 | 32.90 Mn |
| Dec 31, 2024 | 34.06 Mn |
| Sep 30, 2024 | 34.49 Mn |
| Jun 30, 2024 | 35.04 Mn |
| Mar 31, 2024 | 36.78 Mn |
| Dec 31, 2023 | 16.07 Mn |
| Sep 30, 2023 | 14.57 Mn |
| Jun 30, 2023 | 13.85 Mn |
| Mar 31, 2023 | 13.18 Mn |
| Dec 31, 2022 | 14.62 Mn |
| Sep 30, 2022 | 11.33 Mn |
| Jun 30, 2022 | 11.34 Mn |
| Mar 31, 2022 | 10.98 Mn |
| Dec 31, 2021 | 12.26 Mn |
| Sep 30, 2021 | 13.75 Mn |
Opera Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=OPRA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "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=property-plant-and-equipment-net&ticker=OPRA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();