Trade Dad
Worked as a backend developer on a real-time trading application, leveraging the Upstox SDK to integrate live market data, trade execution, and account access with secure API handling and event-based architecture.
Implemented robust authentication flows including signup, login, password update, and JWT-based session management, ensuring secure access and data privacy across all user operations.
Integrated WebSockets using Upstox’s real-time feed to stream live stock market data to connected clients, and designed a system to persist selective metrics (LTP, volume, etc.) into the database every 5 minutes — optimizing backend performance, data storage, and enabling historical analysis.
Key Features
- ▹Real-time market data integration using the Upstox SDK and WebSocket feeds, enabling users to view live stock prices, volumes, and trade activity with minimal latency.
- ▹Secure authentication system with JWT-based session handling, supporting signup, login, and password update flows, built to protect user data and platform access.
- ▹Selective data persistence architecture that stores key metrics like LTP, LTQ, and volume every 5 minutes — balancing performance and historical analytics capability.
- ▹Event-driven backend architecture designed for high-frequency data updates and client broadcasts, ensuring scalable, low-lag delivery of live financial data.
Impact
- ▹Enabled real-time trading insights by integrating Upstox WebSocket feeds and designing an event-driven backend that broadcasts live market data with minimal latency to all connected clients.
- ▹Balanced system performance and analytics by implementing a selective data persistence layer, storing key trading metrics (like LTP, LTQ, and volume) every 5 minutes — enabling historical analysis without overloading the database.
Challenges Overcome
- ▹Handling high-frequency real-time data streams from the Upstox WebSocket feed while maintaining low-latency delivery to all connected clients — requiring an event-driven architecture and efficient memory management.
- ▹Designing a selective data persistence strategy that stores critical metrics like LTP, LTQ, and volume at fixed intervals — balancing database load with the need for accurate historical analytics.
Tech Stack
