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 | 63.1 |
| AI ranki | N/A | #108 |
| Latest closei | N/A | $383.56 |
| 1M returni | N/A | -12.93% |
| 6M returni | N/A | +41.98% |
| 1Y returni | N/A | +21.26% |
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 | $12.13K (+21.3%) started 2025-09-18 |
| 5Y ago | N/A | $7.84K (-21.6%) started 2021-09-20 |
| 10Y ago | N/A | $119.6K (+1096.0%) 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 | -0.12 | 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 | +21.26% |
| CAGRi | N/A | +21.28% | |
| Volatilityi | N/A | 67.31% | |
| Sharpe ratioi | N/A | 0.56 | |
| Sortino ratioi | N/A | 0.83 | |
| Max drawdowni | N/A | 48.72% | |
| Current drawdowni | N/A | 18.79% | |
| Avg drawdowni | N/A | 18.49% | |
| Ulcer Indexi | N/A | 23.58% | |
| Max daily dropi | N/A | 22.24% | |
| Max wkly dropi | N/A | 21.59% | |
| 5Y | Growthi | N/A | -21.61% |
| CAGRi | N/A | -4.76% | |
| Volatilityi | N/A | 70.50% | |
| Sharpe ratioi | N/A | 0.22 | |
| Sortino ratioi | N/A | 0.32 | |
| Max drawdowni | N/A | 76.52% | |
| Current drawdowni | N/A | 34.44% | |
| Avg drawdowni | N/A | 45.88% | |
| Ulcer Indexi | N/A | 48.78% | |
| Max daily dropi | N/A | 26.94% | |
| Max wkly dropi | N/A | 33.71% | |
| 10Y | Growthi | N/A | +1096.01% |
| CAGRi | N/A | +32.10% | |
| Volatilityi | N/A | 65.96% | |
| Sharpe ratioi | N/A | 0.68 | |
| Sortino ratioi | N/A | 1.05 | |
| Max drawdowni | N/A | 76.52% | |
| Current drawdowni | N/A | 34.44% | |
| Avg drawdowni | N/A | 30.93% | |
| Ulcer Indexi | N/A | 37.88% | |
| 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
Want deeper AI forecasts?
This comparison page is public and free forever. Subscribers can unlock saved watchlists, full AI rankings, detailed forecasts, and interactive analysis tools.