Food Delivery Backend System

Scalable backend system enabling real-time order tracking and geo-based restaurant discovery

Problem

Traditional food delivery systems lack real-time order visibility and efficient location-based discovery. Users cannot track orders live, and restaurant filtering becomes inefficient without proximity-based querying.

Solution

Built a backend system using WebSockets for real-time updates and MongoDB geospatial queries for location-based filtering. Designed modular APIs to handle concurrent users efficiently.

System Flow

• • User places order via REST API
• • Order is validated and stored in database
• • WebSocket event is emitted
• • Client receives real-time order updates
• • Restaurant updates propagate instantly

Architecture

API Design

• • POST /orders → Create order
• • GET /restaurants → Fetch nearby restaurants
• • GET /orders/:id → Fetch order details
• • PATCH /orders/:id → Update order status

Data Modeling

• • Used geospatial indexing for restaurant location
• • Designed order schema with status transitions
• • Indexed frequently queried fields for performance

System Highlights

• • Real-time order tracking using WebSockets
• • Geo-based restaurant discovery
• • Scalable REST API design
• • Role-based system architecture

Technical Decisions

• • Used WebSockets instead of polling to reduce latency
• • Used MongoDB geospatial queries for efficient filtering
• • Structured backend using modular architecture
• • Applied indexing to optimize query performance

Scalability

• • WebSockets reduce repeated API calls
• • Database indexing improves read performance
• • Modular architecture supports horizontal scaling

Challenges

• • Managing multiple WebSocket connections
• • Ensuring consistency between real-time updates and database
• • Optimizing geospatial queries for performance

Trade-offs

• • WebSockets increase system complexity
• • Geospatial indexing adds overhead
• • Real-time systems require connection management

Outcome

Improved user experience with live tracking, reduced latency, and built a scalable backend foundation for future expansion.

What I Learned

• • Designing real-time systems using WebSockets
• • Working with geospatial data and indexing
• • Handling concurrency in event-driven systems