Opera (OPRA) EBITDA (2017 - 2026)
Opera (OPRA) recorded EBITDA of $31.34 million in Q2 2026, up 37.8% from $22.74 million a year earlier but down 10.4% from the prior quarter.
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Analysis
Opera (OPRA) EBITDA (2017 - 2026) Analysis & Trends
On a TTM basis, Opera's EBITDA came in at $126.99 million as of Jun 30, 2026, up 18.1% year-over-year; for FY2025, it came in at $108.93 million, up 1.0% from FY2024.
- Annual EBITDA has increased for four straight years, with a five-year compound annual growth rate of 43.4% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $107.84 million in FY2024 (+41.8%), $76.06 million in FY2023 (+36.4%), $55.75 million in FY2022 (+316.4%) and $13.39 million in FY2021 (-25.4%).
- Quarterly EBITDA has ranged from $4.31 million in Q3 2021 to $16.18 billion in Q3 2022 over the past five years.
- On a year-over-year basis, EBITDA has increased for three consecutive quarters, with growth averaging 19.6% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 63.3% in Q2 2024, against a decline of 99.9% in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $34.97 million (Q1 2026), $33.45 million (Q4 2025) and $27.23 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.57 Bn | 240.65 Bn | 2.30 Bn | 693.00 Mn |
| 2 | CrowdStrike Holdings | 232.79 Bn | 213.19 Bn | 1.10 Bn | 170.34 Mn |
| 3 | Fortinet | 125.01 Bn | 110.94 Bn | 1.64 Bn | 827.40 Mn |
| 4 | Snowflake | 112.20 Bn | 99.52 Bn | 1.04 Bn | -134.60 Mn |
| 5 | Datadog | 91.79 Bn | 73.43 Bn | 881.34 Mn | 47.04 Mn |
| 6 | Zscaler | 34.49 Bn | 20.61 Bn | - | - |
| 7 | Okta | 33.78 Bn | 23.88 Bn | 641.00 Mn | 166.00 Mn |
| 8 | Axon Enterprise | 31.92 Bn | 26.44 Bn | 546.45 Mn | 79.24 Mn |
| 9 | MongoDB | 29.36 Bn | 19.83 Bn | 569.77 Mn | 35.33 Mn |
| 10 | Opera | 1.58 Bn | 860.34 Mn | 114.91 Mn | 31.34 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 31.34 Mn |
| Mar 31, 2026 | 34.97 Mn |
| Dec 31, 2025 | 33.45 Mn |
| Sep 30, 2025 | 27.23 Mn |
| Jun 30, 2025 | 22.74 Mn |
| Mar 31, 2025 | 25.51 Mn |
| Dec 31, 2024 | 31.91 Mn |
| Sep 30, 2024 | 113,000.00 |
| Jun 30, 2024 | 65,000.00 |
| Mar 31, 2024 | 22.65 Mn |
| Dec 31, 2023 | 23.55 Mn |
| Sep 30, 2023 | 68,000.00 |
| Jun 30, 2023 | 76,000.00 |
| Mar 31, 2023 | 13.95 Bn |
| Dec 31, 2022 | 11.85 Bn |
| Sep 30, 2022 | 16.18 Bn |
| Jun 30, 2022 | 11.24 Bn |
| Mar 31, 2022 | 4.93 Mn |
| Dec 31, 2021 | 10.09 Mn |
| Sep 30, 2021 | 4.31 Mn |
API Access
Opera EBITDA 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=ebitda&ticker=OPRA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=OPRA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();