Modern AI applications need flexible operational databases for product data and app state.
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Price
$319.16
1D change
-4.08%
Market cap
$25.67B
Sector
Technology
| Metric | MDB |
|---|---|
| Price | $319.16 |
| 1D Change | -4.08% |
| Market Cap | $25.67B |
| Enterprise Value | $23.30B |
| Trailing P/E | -862.6 |
| Forward P/E | 43.5 |
| PEG Ratio | 1.67x |
| Price / Sales | 9.9 |
| EV / Revenue | 9.0 |
| Revenue Growth | 25.2% |
| Earnings Growth | — |
| Gross Margin | 72.0% |
| Operating Margin | -3.6% |
| Net Margin | -1.1% |
| ROE | -1.0% |
| Free Cash Flow | $517.6M |
| FCF Margin | 19.9% |
| Debt / Equity | 2.00x |
| Current Ratio | 4.95x |
| Dividend Yield | — |
| Next Earnings | Aug 26, 2026 |
| Quarterly Revenue | $687.6M |
| Revenue QoQ | -1.1% |
| Quarterly Net Income | $4.4M |
| Net Income QoQ | -71.4% |
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.