MDB vs SNOW Stock Comparison: AI Score, Valuation, Performance and Upside
MongoDB and Snowflake both address AI-era data infrastructure but for different use cases: MongoDB is a developer-centric operational database for building applications, while Snowflake is an analyst-centric analytics warehouse for querying and understanding data at scale. Both are transitioning toward AI workloads — MongoDB through vector search for RAG, Snowflake through Cortex AI inference — but their customer personas and buying processes differ significantly.
MDB vs SNOW is a choice between an operational/transactional database platform (MongoDB) and an analytics/data warehouse platform (Snowflake) — both are cloud-native, both are expanding into AI, but they serve different developer and data engineering personas and should not be seen as direct substitutes.
MDB holds the edge across 4 of 5 key metrics in this comparison. SNOW has delivered stronger 1-year price return (+56.70% vs +20.18%), though MDB has the better forward P/E setup (48.16x vs 113.08x for SNOW). On fundamentals, SNOW is growing revenue faster (33.50%), while MDB maintains the higher operating margin (-3.61%) — a classic growth-versus-profitability split. Analyst consensus implies meaningfully more upside for MDB (+21.62%) than for SNOW (+8.44%).
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.
- prefer a developer-first database platform with broad adoption in application development use cases
- value MongoDB Atlas's multi-cloud architecture and native vector search for AI RAG applications
- want document database exposure to the developer ecosystem transitioning applications from relational to flexible schema models
- are comfortable with relational database incumbents (Oracle, PostgreSQL) and AI-native database competitors as long-term threats
- prefer a cloud data warehouse and analytics platform with a large enterprise data infrastructure customer base
- value Snowflake's multi-cloud data sharing and Data Cloud network effects creating competitive switching costs
- want exposure to AI/ML workload adoption within analytics data platforms through Cortex and Snowpark
- are comfortable with consumption-based revenue model variability and competition from Databricks and BigQuery
| Metric | MDB | SNOW |
|---|---|---|
| AI scorei | 63.1 | 37.2 |
| AI ranki | #108 | #1520 |
| Latest closei | $393.42 | $338.39 |
| 1M returni | -9.48% | +4.01% |
| 6M returni | +45.62% | +92.92% |
| 1Y returni | +20.18% | +56.70% |
How much would $10,000 be worth today if invested at the start of each period, with all dividends reinvested?
| Period | MDB | SNOW |
|---|---|---|
| 1Y ago | $12.47K (+24.7%) started 2025-09-17 | $15.53K (+55.3%) started 2025-09-17 |
| 5Y ago | $7.76K (-22.4%) started 2021-09-17 | $10.48K (+4.8%) started 2021-09-17 |
| 10Y ago | $122.68K (+1126.8%) started 2017-10-19 | $13.33K (+33.3%) started 2020-09-16 |
Hypothetical — past performance does not guarantee future results.
| Metric | MDB | SNOW |
|---|---|---|
| Market capi | $30.02B | $106B |
| Trailing P/Ei | 540.88 | N/A |
| Forward P/Ei | 48.16 | 113.08 |
| Price/Salesi | N/A | N/A |
| EV/Revenuei | 12.51 | 21.99 |
| Analyst targeti | $453.91 | $331.66 |
| Target upsidei | +21.62% | +8.44% |
| Metric | MDB | SNOW |
|---|---|---|
| Revenue growthi | 25.20% | 33.50% |
| Earnings growthi | N/A | N/A |
| EPS growthi | N/A | N/A |
| FCF margini | +19.89% | +34.56% |
| Operating margini | -3.61% | -22.17% |
| Profit margini | -1.12% | -23.79% |
| ROIC proxyi | -0.97% | -54.87% |
| Return on equityi | -0.97% | -54.87% |
| Dividend yieldi | N/A | N/A |
| Payout ratioi | 0.00% | 0.00% |
| Dividend growth streaki | N/A | N/A |
| Betai | 1.54 | 1.31 |
| Debt/equityi | 2.00 | 142.91 |
| Current ratioi | 4.95 | 1.05 |
| Quick ratioi | 4.55 | 0.94 |
Over the past year, MDB and SNOW have moved moderately in the same direction (correlation of 0.61), based on daily returns.
Lower drawdown and smaller single-period drops generally indicate a smoother ride, though they do not guarantee lower future risk.
| Period | Metric | MDB | SNOW |
|---|---|---|---|
| 1Y | Growthi | +24.74% | +55.25% |
| CAGRi | +24.78% | +55.35% | |
| Volatilityi | 67.26% | 65.14% | |
| Sharpe ratioi | 0.60 | 0.92 | |
| Sortino ratioi | 0.89 | 1.62 | |
| Max drawdowni | 48.72% | 56.30% | |
| Current drawdowni | 16.70% | 5.07% | |
| Avg drawdowni | 18.41% | 19.52% | |
| Ulcer Indexi | 23.55% | 25.90% | |
| Max daily dropi | 22.24% | 11.83% | |
| Max wkly dropi | 21.59% | 23.48% | |
| 5Y | Growthi | -22.40% | +4.83% |
| CAGRi | -4.95% | +0.95% | |
| Volatilityi | 70.51% | 62.43% | |
| Sharpe ratioi | 0.21 | 0.25 | |
| Sortino ratioi | 0.32 | 0.38 | |
| Max drawdowni | 76.52% | 72.99% | |
| Current drawdowni | 32.75% | 15.80% | |
| Avg drawdowni | 45.86% | 51.97% | |
| Ulcer Indexi | 48.77% | 54.53% | |
| Max daily dropi | 26.94% | 18.14% | |
| Max wkly dropi | 33.71% | 28.56% | |
| 10Y | Growthi | +1126.75% | +33.26% |
| CAGRi | +32.49% | +4.90% | |
| Volatilityi | 65.97% | 62.20% | |
| Sharpe ratioi | 0.69 | 0.31 | |
| Sortino ratioi | 1.05 | 0.47 | |
| Max drawdowni | 76.52% | 72.99% | |
| Current drawdowni | 32.75% | 15.80% | |
| Avg drawdowni | 30.93% | 48.06% | |
| Ulcer Indexi | 37.88% | 51.28% | |
| Max daily dropi | 26.94% | 18.14% | |
| Max wkly dropi | 33.71% | 28.56% |
| Category | MDB | SNOW |
|---|---|---|
| Company | MongoDB, Inc. | Snowflake Inc. |
| Sector | Technology | Technology |
| Industry | Software - Infrastructure | Software - Application |
| Core business | MongoDB provides a developer-friendly document database (MongoDB Atlas, the cloud version, and Community/Enterprise Server for on-premises). MongoDB's document model allows developers to store data in flexible JSON-like structures without predefined schemas, enabling faster application development versus traditional relational databases. Atlas — the cloud-hosted managed version — is the primary growth driver, offered across AWS, Azure, and GCP. MongoDB is expanding into vector search for AI retrieval-augmented generation (RAG) use cases. | Snowflake provides a cloud-native data warehouse and data platform for analytics workloads, operating on AWS, Azure, and GCP. Its separation of compute from storage allows customers to scale independently and pay only for what they use, disrupting traditional on-premises data warehouse licensing. Snowflake is expanding from analytics into AI/ML workloads through Snowflake Cortex (LLM inference), Snowpark (Python/Java/Scala in the Snowflake runtime), and data collaboration through Snowflake Marketplace. |
| Investor focus | Investors track Atlas ARR growth, net revenue retention rate (indicating Atlas expansion within existing customers), the pace of AI vector search adoption for RAG applications, and gross margin improvement as Atlas operational efficiency improves. | Investors focus on product revenue growth (consumption-based), net revenue retention rate (historically above 120%), Snowflake Cortex and AI workload adoption, and the trajectory of operating margins as the company scales toward profitability. |
- Developer-first document database with the largest market adoption of any non-relational database globally
- Atlas multi-cloud deployment across AWS, Azure, and GCP removes cloud vendor lock-in, accelerating enterprise adoption
- Native vector search in Atlas positions MongoDB as an AI data platform for RAG applications without requiring separate vector database vendors
- Multi-cloud data platform architecture separates compute from storage, enabling efficient scaling that traditional data warehouses cannot match
- Snowflake Data Cloud enables secure data sharing between organizations, creating network effects that competitors cannot easily replicate
- Cortex AI and Snowpark are expanding Snowflake from analytics into AI/ML inference and application development workloads
- Large language models and AI are changing application architectures — some developers use AI-native databases that may reduce MongoDB's traditional use cases
- Amazon DocumentDB offers a MongoDB-compatible API on AWS at lower cost, creating pricing pressure for Atlas in AWS-focused deployments
- MongoDB's growth rate has decelerated as the company laps the post-COVID digital transformation build-up
- Growth has decelerated significantly from the post-IPO period as initial deployment intensity moderated
- Databricks competes directly in Spark-based data engineering and is partnering with AI platforms against Snowflake's analytics dominance
- Consumption-based revenue creates lumpy quarterly results as customers optimize their Snowflake credit usage during macro-cautious periods
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