Modern AI applications need flexible operational databases for product data and app state.
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Price
$427.69
1D change
+6.19%
Market cap
$34.40B
Sector
Technology
| Metric | MDB |
|---|---|
| Price | $427.69 |
| 1D Change | +6.19% |
| Market Cap | $34.40B |
| Enterprise Value | $32.10B |
| Trailing P/E | 585.9 |
| Forward P/E | 54.9 |
| PEG Ratio | 1.67x |
| Price / Sales | 12.4 |
| EV / Revenue | 11.5 |
| Revenue Growth | 30.5% |
| Earnings Growth | — |
| Gross Margin | 72.7% |
| Operating Margin | 3.7% |
| Net Margin | 2.1% |
| ROE | 2.0% |
| Free Cash Flow | $561.4M |
| FCF Margin | 20.2% |
| Debt / Equity | 1.85x |
| Current Ratio | 4.87x |
| Dividend Yield | 0.00% |
| Next Earnings | Dec 01, 2026 |
| Quarterly Revenue | $771.8M |
| Revenue QoQ | +12.2% |
| Quarterly Net Income | $40.9M |
| Net Income QoQ | +823.3% |
MDB thesis lens
Developer data platform
Why it could benefit
- Modern AI applications need flexible operational databases for product data and app state.
- Atlas can participate as developers build AI-native apps in the cloud.
- Vector-search and data services make MongoDB more relevant to AI application stacks.
Moat / edge
- Large developer ecosystem.
- Managed Atlas cloud platform with recurring usage.
- Flexible document model suited to modern applications.
What to watch
- Atlas growth and workload expansion.
- AI application use cases and vector-search adoption.
- Competitive pressure from cloud-native databases.
Key risks
- Usage growth can slow with cloud cost optimization.
- Database competition is intense and price-sensitive.