Aurora Mobile (JG) Accumulated Expenses (2017 - 2026)
Aurora Mobile's Accumulated Expenses was $8.54 million in Q2 2026, up 9.4% from $7.8 million a year earlier but down 3.0% from the prior quarter.
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Analysis
Aurora Mobile (JG) Accumulated Expenses (2017 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Aurora Mobile came in at $9.57 million, up 2.2% from FY2024.
- Accumulated Expenses shows a five-year compound annual growth rate of 98.7% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $9.36 million in FY2024 (+2.3%), $9.15 million in FY2023 (-14.5%), $10.7 million in FY2022 and $354,000 in FY2021 (+14.6%).
- Quarterly Accumulated Expenses has moved between $388,521 (Q4 2021) and $14.76 million (Q3 2021) over five years.
- Compared with a year earlier, Accumulated Expenses was higher in four of the last eight quarters, with growth averaging 1.4%.
- The best year-over-year quarter for Accumulated Expenses over five years was Q4 2021 (growth of 27.6%); the worst was Q1 2023 (a decline of 27.5%).
- Per Business Quant data, JG's Accumulated Expenses in the three quarters before Q2 2026 was $8.8 million (Q1 2026), $9.43 million (Q4 2025) and $10.16 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | Aurora Mobile | 4.83 Bn | 4.76 Bn | 10.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 8.54 Mn |
| Mar 31, 2026 | 8.80 Mn |
| Dec 31, 2025 | 9.43 Mn |
| Sep 30, 2025 | 10.16 Mn |
| Jun 30, 2025 | 7.80 Mn |
| Mar 31, 2025 | 9.15 Mn |
| Dec 31, 2024 | 9.52 Mn |
| Sep 30, 2024 | 9.69 Mn |
| Jun 30, 2024 | 8.35 Mn |
| Mar 31, 2024 | 8.85 Mn |
| Dec 31, 2023 | 9.02 Mn |
| Sep 30, 2023 | 9.73 Mn |
| Jun 30, 2023 | 9.08 Mn |
| Mar 31, 2023 | 9.50 Mn |
| Dec 31, 2022 | 10.37 Mn |
| Sep 30, 2022 | 12.41 Mn |
| Jun 30, 2022 | 9.65 Mn |
| Mar 31, 2022 | 13.10 Mn |
| Dec 31, 2021 | 388,521.42 |
| Sep 30, 2021 | 14.76 Mn |
API Access
Aurora Mobile Accumulated Expenses 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=accumulated-expenses&ticker=JG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "JG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=JG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();