CFLT vs MDB Stock Comparison: AI Score, Valuation, Performance and Upside
CFLT and MDB are both modern cloud data infrastructure companies serving different data management needs — Confluent for real-time streaming data pipelines and event-driven architectures, MongoDB for flexible application database storage and retrieval. Both are well-positioned for AI-driven application development trends.
CFLT vs MDB compares two modern cloud data platforms: Confluent's real-time streaming infrastructure versus MongoDB's flexible document database, both serving the data backbone needs of modern application development.
CFLT and MDB are closely matched — they split the tracked metrics evenly.
Human Wall Street analysts' price targets, typically implying a ~12-month view — a separate signal from this site's own AI Prediction Signal further down the page, which is a 5-/30-day machine-learning forecast based on price history alone.
- Want exposure to real-time data streaming infrastructure built on the Apache Kafka standard
- Believe AI and event-driven application architectures will drive sustained demand for streaming platforms
- See Confluent as essential middleware for connecting real-time data across enterprise systems
- Want exposure to a leading cloud database platform with strong developer adoption and AI application positioning
- Value MongoDB Atlas's flexible document model for modern application development needs
- Believe vector search and AI-native database features will drive continued platform expansion
| Metric | CFLT | MDB |
|---|---|---|
| AI scorei | N/A | 55.6 |
| AI ranki | N/A | #90 |
| Latest closei | N/A | $335.37 |
How much would $10,000 be worth today if invested at the start of each period, with all dividends reinvested?
| Period | CFLT | MDB |
|---|---|---|
| 1Y ago | N/A | $9.42K (-5.8%) started 2025-11-04 |
| 5Y ago | N/A | $6.27K (-37.3%) started 2021-11-04 |
| 10Y ago | N/A | $104.57K (+945.7%) started 2017-10-19 |
Hypothetical — past performance does not guarantee future results.
| Metric | CFLT | MDB |
|---|---|---|
| Market capi | N/A | $30.02B |
| Trailing P/Ei | N/A | 540.88 |
| Forward P/Ei | N/A | 48.16 |
| Price/Salesi | 9.54 | N/A |
| EV/Revenuei | N/A | 12.51 |
| Analyst targeti | N/A | $453.91 |
| Target upsidei | N/A | +21.62% |
| Metric | CFLT | MDB |
|---|---|---|
| Revenue growthi | N/A | 25.20% |
| Earnings growthi | N/A | N/A |
| EPS growthi | N/A | N/A |
| FCF margini | N/A | +19.89% |
| Operating margini | N/A | -3.61% |
| Profit margini | N/A | -1.12% |
| ROIC proxyi | N/A | -0.97% |
| Return on equityi | N/A | -0.97% |
| Dividend yieldi | N/A | N/A |
| Payout ratioi | N/A | 0.00% |
| Dividend growth streaki | N/A | N/A |
| Betai | -0.15 | 1.54 |
| Debt/equityi | N/A | 2.00 |
| Current ratioi | N/A | 4.95 |
| Quick ratioi | N/A | 4.55 |
Lower drawdown and smaller single-period drops generally indicate a smoother ride, though they do not guarantee lower future risk.
| Period | Metric | CFLT | MDB |
|---|---|---|---|
| 1Y | Growthi | N/A | -5.75% |
| CAGRi | N/A | -5.76% | |
| Volatilityi | N/A | 73.17% | |
| Sharpe ratioi | N/A | 0.23 | |
| Sortino ratioi | N/A | 0.32 | |
| Max drawdowni | N/A | 48.72% | |
| Current drawdowni | N/A | 28.99% | |
| Avg drawdowni | N/A | 20.96% | |
| Ulcer Indexi | N/A | 24.86% | |
| Max daily dropi | N/A | 22.24% | |
| Max wkly dropi | N/A | 21.59% | |
| 5Y | Growthi | N/A | -37.32% |
| CAGRi | N/A | -8.92% | |
| Volatilityi | N/A | 71.45% | |
| Sharpe ratioi | N/A | 0.16 | |
| Sortino ratioi | N/A | 0.24 | |
| Max drawdowni | N/A | 76.52% | |
| Current drawdowni | N/A | 42.67% | |
| Avg drawdowni | N/A | 46.73% | |
| Ulcer Indexi | N/A | 49.15% | |
| Max daily dropi | N/A | 26.94% | |
| Max wkly dropi | N/A | 33.71% | |
| 10Y | Growthi | N/A | +945.74% |
| CAGRi | N/A | +29.64% | |
| Volatilityi | N/A | 66.27% | |
| Sharpe ratioi | N/A | 0.65 | |
| Sortino ratioi | N/A | 0.99 | |
| Max drawdowni | N/A | 76.52% | |
| Current drawdowni | N/A | 42.67% | |
| Avg drawdowni | N/A | 31.00% | |
| Ulcer Indexi | N/A | 37.86% | |
| Max daily dropi | N/A | 26.94% | |
| Max wkly dropi | N/A | 33.71% |
| Category | CFLT | MDB |
|---|---|---|
| Company | Confluent, Inc. | MongoDB, Inc. |
| Sector | Information Technology - Data Streaming | Technology |
| Industry | N/A | Software - Infrastructure |
| Core business | Confluent provides a cloud-native data streaming platform built on Apache Kafka, enabling organizations to build real-time data pipelines, event-driven applications, and streaming analytics across their entire data infrastructure. | MongoDB provides a flexible document-oriented database platform used by developers to store, query, and process diverse data structures, with its Atlas cloud database service increasingly serving as the core of modern application backends. |
| Investor focus | Investors track Confluent's cloud revenue growth (the faster-growing, higher-margin portion), total revenue and consumption trends, and the development of the Flink stream processing capabilities as part of its platform. | Investors track MongoDB Atlas cloud revenue growth, monthly active customers on Atlas, net new Annual Recurring Revenue, and the platform's expansion into AI-relevant workloads including vector search for AI application development. |
- Created and leads the commercial ecosystem around Apache Kafka — the industry standard for high-throughput real-time data streaming
- Confluent Cloud enables organizations to consume streaming data without managing Kafka infrastructure themselves
- Real-time data streaming is increasingly essential infrastructure for AI applications, financial systems, and event-driven architectures
- Leading developer-facing database platform with MongoDB Atlas providing a fully managed cloud service
- Document model flexibility makes MongoDB well-suited for modern application development with diverse, evolving data structures
- Vector search capabilities position MongoDB as an infrastructure layer for AI application development
- Confluent Cloud revenue is driven by consumption rather than fixed subscriptions, creating revenue variability with customer usage patterns
- Must continue proving the value of its commercial platform versus self-managed Kafka
- Faces competition from cloud providers (AWS Kinesis, Azure Event Hubs) offering streaming as part of their native cloud services
- Database market is highly competitive with AWS DynamoDB, Google Firestore, and relational databases from all cloud providers
- Atlas growth has moderated from earlier hyper-growth as the market becomes more competitive
- AI application workloads may shift some query patterns toward more specialized vector or graph databases
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