StarSwap
High-performance decentralized crypto swap with distributed rate limiting and concurrent transaction handling
Role
Lead Backend Engineer
Timeline
January 2026
Infrastructure
Vercel Frontend, Railway Backend, Redis Cloud
01. The Problem
Traditional decentralized exchanges often struggle with frontend-to-backend synchronization and handling high-frequency swap requests without overloading the database or exposing the system to race conditions during state updates.
02. Architecture
StarSwap implements a decoupled architecture where the Next.js frontend communicates with an Express/Redis backend. We used Redis for atomic state management and distributed rate limiting to ensure system stability under load.
03. Tech Stack
04. Optimization
Implemented Redis Token Bucket for distributed rate limiting
Used Prisma transaction isolation levels to prevent double-spending in virtual accounts
Optimized frontend bundle size by 40% using dynamic imports and tree shaking
StarSwap: Building a Scalable Crypto Infrastructure
StarSwap is a flagship project designed to demonstrate the feasibility of building high-throughput financial systems using modern web technologies.
Technical Depth
The project focuses on the core challenges of financial software: Accuracy, Speed, and Reliability.
Distributed Rate Limiting
We implemented a Token Bucket algorithm in Redis. This ensures that even with multiple backend instances, the global rate limit for each user is strictly enforced.
async function checkRateLimit(userId: string) {
const tokens = await redis.get(`tokens:${userId}`);
if (parseInt(tokens) > 0) {
await redis.decr(`tokens:${userId}`);
return true;
}
return false;
}Atomic State Updates
To prevent race conditions during swaps, we utilized PostgreSQL's SELECT FOR UPDATE via Prisma, ensuring that a user's balance is locked during the transaction process.
Visual Excellence
The UI was built with a focus on "Data Density" and "Financial Clarity," using premium dark mode aesthetics and real-time update indicators.
Challenges
Ensuring atomic balance updates in a concurrent environment
Implementing efficient rate limiting without introducing latency
Scaling the backend to handle high transaction volumes
Learnings
Distributed state management with Redis
Advanced database transaction patterns
Optimizing Next.js for high-performance dashboards


