MongoDB Competitors
| MDB Stock | USD 260.68 -9.89 -3.66% |
MongoDB vs Check Point Correlation Summary
Very poor diversification
The correlation between MDB and CHKP is 0.86, which Macroaxis classifies as Very poor diversification for the selected horizon. Used correctly, the chart helps investors judge whether adding the second position genuinely diversifies the first.
Moving together with MongoDB Stock
Moving against MongoDB Stock
The concept of mean reversion suggests that MongoDB's price will eventually return toward its long-run average. High prices may deter value investors, while unusually low prices often attract buyers who anticipate a recovery.
MongoDB Competition Correlation Matrix
Correlation analysis between MongoDB and its competitors helps investors understand whether diversification is real or only superficial inside the same peer group. This matrix is most informative when investors want to know whether adding another peer would improve diversification, increase crowding, or leave total risk largely unchanged.
High positive correlations
| High negative correlations
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Risk-Adjusted Indicators
There is a big difference between MongoDB Stock performing well and MongoDB Company doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze MongoDB's multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.| Mean Deviation | Jensen Alpha | Sortino Ratio | Treynor Ratio | Semi Deviation | Expected Shortfall | Potential Upside | Value @Risk | Maximum Drawdown | ||
|---|---|---|---|---|---|---|---|---|---|---|
| CYBR | 1.43 | -0.30 | 0.00 | -0.90 | 0.00 | 2.63 | 10.19 | |||
| SMCI | 2.86 | 0.02 | 0.00 | -0.04 | 0.00 | 8.25 | 22.40 | |||
| IOT | 2.74 | -0.42 | 0.00 | -0.55 | 0.00 | 5.46 | 23.23 | |||
| SNDK | 5.02 | 1.87 | 0.32 | 0.65 | 4.82 | 12.81 | 43.52 | |||
| VRSN | 1.13 | -0.09 | 0.00 | 0.58 | 0.00 | 2.77 | 10.51 | |||
| TER | 2.76 | 0.72 | 0.17 | 0.25 | 3.03 | 7.23 | 24.05 | |||
| AFRM | 2.87 | -0.44 | 0.00 | -0.34 | 0.00 | 6.01 | 23.76 | |||
| ZM | 1.95 | -0.15 | 0.00 | -0.18 | 0.00 | 3.85 | 22.86 | |||
| CRDO | 3.88 | -0.56 | 0.00 | 3.11 | 0.00 | 9.16 | 28.42 | |||
| CHKP | 1.58 | -0.28 | 0.00 | -0.50 | 0.00 | 2.64 | 9.44 |
Peer Comparison: Net Income
Net income is one of the most important fundamental items in finance. It plays a large role in MongoDB financial statement analysis. It represents the amount of money remaining after all of MongoDB operating expenses, interest, taxes and preferred stock dividends have been deducted from a company total revenue.Compare MongoDB and related stocks such as CyberArk Software, Super Micro Computer, and Samsara Net Income Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CYBR | 5.9 M | 5.9 M | 7.9 M | 6.6 M | 10 M | 25.8 M | 28.1 M | 16 M | 47.1 M | 63.1 M | -5.8 M | -83.9 M | -130.4 M | -66.5 M | -93.5 M | -146.9 M | -139.6 M |
| SMCI | 2.2 M | 29.6 M | 21.2 M | 54.1 M | 101.9 M | 72.1 M | 66.9 M | 46.2 M | 71.9 M | 84.3 M | 111.9 M | 285.2 M | 640 M | 1.2 B | 1 B | 1.2 B | 1.3 B |
| IOT | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -225.2 M | -210.2 M | -355 M | -247.4 M | -286.7 M | -154.9 M | -9.1 M | -9.6 M |
| SNDK | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | 1.1 B | -2.1 B | -672 M | -1.6 B | -1.5 B | -1.4 B |
| VRSN | -19.2 M | 142.9 M | 320 M | 544.5 M | 355.3 M | 375.2 M | 440.6 M | 457.2 M | 582.5 M | 612.3 M | 814.9 M | 784.8 M | 673.8 M | 817.6 M | 785.7 M | 825.7 M | 867 M |
| TER | 20.2 M | 349.4 M | 217 M | 164.9 M | 81.3 M | 206.5 M | -43.4 M | 257.7 M | 451.8 M | 467.5 M | 784.1 M | 1 B | 715.5 M | 448.8 M | 542.4 M | 554 M | 581.7 M |
| AFRM | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -120.5 M | -112.6 M | -441 M | -707.4 M | -985.3 M | -517.8 M | 52.2 M | 47 M | 49.3 M |
| ZM | -14 K | -14 K | -14 K | -14 K | -14 K | -14 K | -14 K | -3.8 M | 7.6 M | 25.3 M | 672.3 M | 1.4 B | 103.7 M | 637.5 M | 1 B | 1.9 B | 2 B |
| CRDO | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | 1.3 M | -27.5 M | -22.2 M | -16.5 M | -28.4 M | 52.2 M | 60 M | 63 M |
| CHKP | 15.2 M | 544 M | 620 M | 652.8 M | 659.6 M | 685.9 M | 724.8 M | 802.9 M | 821.3 M | 825.7 M | 846.6 M | 815.6 M | 796.9 M | 840.3 M | 845.7 M | 1.1 B | 552.3 M |
MongoDB Competitive Analysis
MongoDB's competitive standing becomes clearer when measured alongside CyberArk Software, Super Micro, and Samsara. With 2.46 B in revenue and a 21.78 B market value, MongoDB anchors one end of the peer spectrum. The -2.48% return on equity and -2.89% profit margin point to near-term profitability challenges for MongoDB. MongoDB keeps more of each revenue dollar with a -2.89% margin versus -10.79% at CyberArk Software. Super Micro leads on revenue, 21.97 B to 2.46 B, a substantial gap. Samsara leads with -0.73% return on equity versus -2.48% for MongoDB.| Better Than Average | Worse Than Peers | View Performance Chart |
Peer Performance Charts
How to Analyze MongoDB Against Peers
MongoDB's peer analysis compares MongoDB with related companies to put valuation, quality, and risk metrics in context. This helps determine whether recent performance is company-specific or broadly sector-driven. A practical workflow includes:- Set a relevant peer group: Include direct competitors and close alternatives with comparable business exposure.
- Benchmark core financials: Compare profitability, growth, capital structure, and cash flow quality.
- Check valuation dispersion: Review whether MongoDB trades at a premium or discount versus peers and why.
- Evaluate risk profile: Compare volatility, drawdowns, and correlation to avoid false diversification assumptions.
- Document the thesis: Record where MongoDB leads or lags and what catalysts could close or widen the gap.