StatX is a scalable, real-time company metric visualization platform built using the MERN stack. Designed for high concurrency, it enables users to log in, search for companies, view detailed metrics, and access historical data in an intuitive interface.
Project Demo 🎬 - Watch Video
- Built with React.
- Features:
- User-friendly interface with responsive design powered by RSUITE and custom CSS.
- State management with React’s
useState,useEffect, and Context API. - Data visualization with interactive graphs and tables for real-time metrics.
- Built with Node.js and Express, containerized with Docker.
- Features:
- Scalable REST API for authentication, data fetching, and real-time calculations.
- Redis caching for lightning-fast responses.
- MongoDB Atlas for scalable and secure data storage (sharded for horizontal scaling).
- Authentication via Google and GitHub OAuth, with JWT tokens and 2FA (Speakeasy).
- Login: Users authenticate via Google or GitHub (2FA optional).
- Search: Enter a company name or code.
- Compute: Backend processes metrics like stock prices, market share, and diversity in real time.
- Visualize: Results are displayed on interactive graphs, with history for comparisons.
| Component | Technology | Features |
|---|---|---|
| Frontend | React + RSUITE | Responsive UI, data visualization, React Router for navigation. |
| Backend | Node.js + Express | REST API, scalable containerized deployment using Docker with Nginx. |
| Database | MongoDB Atlas | Sharded NoSQL database for real-time data storage and historical metrics. |
| Caching | Redis | Improves response times for high concurrency requests. |
| Authentication | OAuth + JWT + 2FA | Secure login with Google/GitHub, token-based authentication, and two-factor security. |
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Frontend:
- Automatically scales on Render for high user traffic.
-
Backend:
- Dockerized environment supports multiple instances with Nginx for load balancing.
- Redis caching ensures minimal latency during real-time computations.
-
Database:
- MongoDB Atlas scales horizontally with sharding, providing fast and efficient queries.
- Machine Learning:
- Implemented XGBoost Regression for predictive analytics.
- Historical data used to forecast future metrics with weighted dynamic adjustments.
- Modular, clean codebase.
- CI/CD pipelines for seamless deployment.
- GitHub for version control.
- RSUITE for responsive and elegant design.
- Interactive graphs and tables for data comparison.
- Robust security with 2FA and password recovery options.
- User Data: Credentials and 2FA setup.
- Company Data: Stock prices, market share, revenue, and diversity metrics.
- Normalization & Cleanup: Duplicate removal and handling of missing fields.