Opera (OPRA) Receivables (2017 - 2026)
Opera (OPRA) posted Receivables of $129.1 million for Q2 2026, up 25.0% from $103.29 million a year earlier and up 12.8% from the prior quarter.
Powered by 
Analysis
Opera (OPRA) Receivables (2017 - 2026) Analysis & Trends
At the end of FY2025, Opera's Receivables came in at $119.63 million, up 22.8% from FY2024.
- Annual Receivables has increased for five consecutive years, with a five-year compound annual growth rate of 24.2% (FY2020 to FY2025).
- In prior years, Opera's Receivables was $97.38 million in FY2024 (+26.2%), $77.14 million in FY2023 (+2.6%), $75.17 million in FY2022 (+20.5%) and $62.4 million in FY2021 (+54.1%).
- The Q2 2026 figure stands as the highest quarterly Receivables in data going back to Q3 2017.
- On a year-over-year basis, Receivables has increased in each of the last 20 quarters, with growth averaging 30.2% over the last eight quarters.
- Over the past five years, the year-over-year growth in Receivables ranged from 2.6% (Q4 2023) to 57.5% (Q1 2025).
- According to Business Quant data, Receivables for the three prior quarters was $114.44 million (Q1 2026), $119.63 million (Q4 2025) and $108.25 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.42 Bn | 240.49 Bn | 2.30 Bn | 3.63 Bn |
| 2 | CrowdStrike Holdings | 232.07 Bn | 212.47 Bn | 1.10 Bn | 1.04 Bn |
| 3 | Fortinet | 125.35 Bn | 111.28 Bn | 1.64 Bn | 1.46 Bn |
| 4 | Snowflake | 111.63 Bn | 98.94 Bn | 1.04 Bn | 718.46 Mn |
| 5 | Datadog | 91.35 Bn | 72.99 Bn | 881.34 Mn | 975.55 Mn |
| 6 | Zscaler | 34.43 Bn | 20.55 Bn | - | 1.15 Bn |
| 7 | Okta | 33.87 Bn | 23.97 Bn | 641.00 Mn | 469.00 Mn |
| 8 | Axon Enterprise | 31.65 Bn | 26.18 Bn | 546.45 Mn | 1.52 Bn |
| 9 | MongoDB | 29.46 Bn | 19.93 Bn | 569.77 Mn | 483.22 Mn |
| 10 | Opera | 1.58 Bn | 854.52 Mn | 114.91 Mn | 129.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 129.10 Mn |
| Mar 31, 2026 | 114.44 Mn |
| Dec 31, 2025 | 119.63 Mn |
| Sep 30, 2025 | 108.25 Mn |
| Jun 30, 2025 | 103.29 Mn |
| Mar 31, 2025 | 108.48 Mn |
| Dec 31, 2024 | 97.38 Mn |
| Sep 30, 2024 | 79.16 Mn |
| Jun 30, 2024 | 70.64 Mn |
| Mar 31, 2024 | 68.87 Mn |
| Dec 31, 2023 | 77.14 Mn |
| Sep 30, 2023 | 65.24 Mn |
| Jun 30, 2023 | 60.14 Mn |
| Mar 31, 2023 | 56.29 Mn |
| Dec 31, 2022 | 75.17 Mn |
| Sep 30, 2022 | 62.74 Mn |
| Jun 30, 2022 | 52.96 Mn |
| Mar 31, 2022 | 46.81 Mn |
| Dec 31, 2021 | 62.40 Mn |
| Sep 30, 2021 | 47.48 Mn |
API Access
Opera Receivables 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=receivables&ticker=OPRA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "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=receivables&ticker=OPRA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();