MongoDB (MDB) Total Liabilities (2017 - 2026)
MongoDB's Total Liabilities was $797.71 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 33.2% from $599.09 million a year earlier and up 5.3% from the prior quarter.
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Analysis
MongoDB (MDB) Total Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2026 (ended Jan 31, 2026), Total Liabilities at MongoDB came in at $806.49 million, up 24.4% from FY2025.
- Total Liabilities shows a five-year compound annual growth rate of -10.6% (FY2021 to FY2026).
- In earlier fiscal years, Total Liabilities was $648.07 million in FY2025 (-64.0%), $1.8 billion in FY2024 (-2.6%), $1.85 billion in FY2023 (+3.7%) and $1.78 billion in FY2022 (+26.2%).
- Quarterly Total Liabilities has moved between $591.47 million (fiscal Q1 2026) and $1.85 billion (fiscal Q4 2023) over five years.
- Compared with a year earlier, Total Liabilities has increased for three straight quarters, with an average decline of 21.5% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was fiscal Q2 2027 (growth of 33.2%); the worst was fiscal Q1 2026 (a decline of 66.5%).
- Per Business Quant data, MDB's Total Liabilities in the three fiscal quarters before Q2 2027 was $757.73 million (Q1 2027), $806.49 million (Q4 2026) and $678.21 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 305.41 Bn | 290.49 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 258.16 Bn | 238.60 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 127.25 Bn | 113.18 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 118.44 Bn | 105.76 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.25 Bn | 77.89 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Axon Enterprise | 34.94 Bn | 29.46 Bn | 546.45 Mn | 3.81 Bn |
| 7 | MongoDB | 33.06 Bn | 23.53 Bn | 569.77 Mn | 797.71 Mn |
| 8 | Okta | 32.62 Bn | 22.72 Bn | 641.00 Mn | 2.17 Bn |
| 9 | Zscaler | 31.48 Bn | 17.60 Bn | - | 5.27 Bn |
| 10 | Baidu | 29.71 Bn | -43.91 Bn | 1.47 Mn | 27.69 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 797.71 Mn |
| Apr 30, 2026 | 757.73 Mn |
| Jan 31, 2026 | 806.49 Mn |
| Oct 31, 2025 | 678.21 Mn |
| Jul 31, 2025 | 599.09 Mn |
| Apr 30, 2025 | 591.47 Mn |
| Jan 31, 2025 | 648.07 Mn |
| Oct 31, 2024 | 1.72 Bn |
| Jul 31, 2024 | 1.77 Bn |
| Apr 30, 2024 | 1.77 Bn |
| Jan 31, 2024 | 1.80 Bn |
| Oct 31, 2023 | 1.73 Bn |
| Jul 31, 2023 | 1.76 Bn |
| Apr 30, 2023 | 1.79 Bn |
| Jan 31, 2023 | 1.85 Bn |
| Oct 31, 2022 | 1.78 Bn |
| Jul 31, 2022 | 1.78 Bn |
| Apr 30, 2022 | 1.76 Bn |
| Jan 31, 2022 | 1.78 Bn |
| Oct 31, 2021 | 1.69 Bn |
API Access
MongoDB Total Liabilities 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=total-liabilities&ticker=MDB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=MDB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();