MongoDB (MDB) Operating Expenses (2016 - 2026)
MongoDB (MDB) reported Operating Expenses of $541.37 million for fiscal Q2 2027 (quarter ended Jul 31, 2026), up 11.6% from $485.27 million a year earlier and up 3.9% from the prior quarter.
MongoDB (MDB) Operating Expenses (2016 - 2026) Analysis & Trends
Over the twelve months ended Jul 31, 2026, MongoDB's Operating Expenses came in at $2.04 billion, up 15.1% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $1.9 billion, up 12.9% from FY2025.
- Operating Expenses has increased for ten consecutive fiscal years, with a five-year compound annual growth rate of 25.1% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $1.69 billion in FY2025 (+13.1%), $1.49 billion in FY2024 (+16.5%), $1.28 billion in FY2023 (+41.8%) and $903.65 million in FY2022 (+45.1%).
- The fiscal Q2 2027 figure ranks as the highest quarterly Operating Expenses in data going back to fiscal Q3 2017.
- Year over year, Operating Expenses has now increased in each of the last 36 quarters, with growth averaging 11.9% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 0.9% in fiscal Q4 2025 to 56.8% in fiscal Q2 2023.
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $520.98 million (Q1 2027), $507.36 million (Q4 2026) and $467.56 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 256.01 Bn | 241.08 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 231.46 Bn | 211.86 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 123.83 Bn | 109.76 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 107.27 Bn | 94.59 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 88.05 Bn | 69.69 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 33.23 Bn | 19.35 Bn | - | - |
| 7 | Okta | 32.56 Bn | 22.66 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 31.41 Bn | 25.93 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 27.26 Bn | 17.73 Bn | 569.77 Mn | 541.37 Mn |
| 10 | F5 | 25.06 Bn | 19.47 Bn | 711.51 Mn | 498.25 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 541.37 Mn |
| Apr 30, 2026 | 520.98 Mn |
| Jan 31, 2026 | 507.36 Mn |
| Oct 31, 2025 | 467.56 Mn |
| Jul 31, 2025 | 485.27 Mn |
| Apr 30, 2025 | 444.53 Mn |
| Jan 31, 2025 | 417.95 Mn |
| Oct 31, 2024 | 421.92 Mn |
| Jul 31, 2024 | 421.30 Mn |
| Apr 30, 2024 | 426.05 Mn |
| Jan 31, 2024 | 414.33 Mn |
| Oct 31, 2023 | 371.10 Mn |
| Jul 31, 2023 | 367.46 Mn |
| Apr 30, 2023 | 339.38 Mn |
| Jan 31, 2023 | 345.10 Mn |
| Oct 31, 2022 | 322.89 Mn |
| Jul 31, 2022 | 330.23 Mn |
| Apr 30, 2022 | 283.17 Mn |
| Jan 31, 2022 | 269.32 Mn |
| Oct 31, 2021 | 235.20 Mn |
MongoDB Operating 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=operating-expenses&ticker=MDB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MDB", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=MDB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();