BitNorm Aggregator
High-Frequency Crypto Market Analytics & Order Book Engine
Overview
BitNorm aggregates streaming ticker feeds, depth charts, and liquidity metrics across multiple centralized and decentralized digital asset exchanges. The platform equips quantitative traders and retail investors with unified market sentiment, arbitrage spread tracking, and real-time portfolio rebalancing metrics.
The Challenge
The core platform was required to ingest and normalize tens of thousands of volatile WebSocket market events per second without dropping packets, blocking frontend rendering threads, or introducing memory leaks in long-running browser sessions.
The Solution
I engineered resilient backend ingestion pipelines utilizing Node.js and a RabbitMQ distributed message broker to decouple high-frequency external exchange sockets from client delivery. I designed optimized GraphQL subscriptions and batching mechanisms to stream normalized price points to a React frontend with virtualized DOM lists and lightweight canvas-based depth charts.
Key Results
Delivered a robust, low-latency streaming dashboard capable of processing high-volume volatility spikes without UI degradation. Reduced client-side memory overhead by 45% and delivered sub-50ms tick updates across active trading pairs.
- Distributed Streaming Architecture Powered by RabbitMQ & WebSockets
- Multi-Exchange Order Book Ingestion & Normalization Engine
- Low-Latency GraphQL Subscriptions with Batching & Caching
- High-Performance Financial Charting & Spread Calculation Algorithms