Low-Latency Big Data Parsing Engine
Multi-protocol real-time data streams for algorithmic trading
<200ms
End-to-end latency
99.9%
Uptime
50K+
Events per second
The Problem
Algorithmic trading on decentralized exchanges requires processing massive volumes of real-time data from multiple protocols simultaneously. Existing solutions couldn't maintain the sub-second latency required for competitive trade execution while handling the unpredictable burst patterns of blockchain data.
The Solution
Built a multi-protocol ingestion layer that normalizes heterogeneous data feeds into a unified stream. Applied backpressure-aware buffering and parallel processing pipelines to maintain consistent latency under load. Implemented circuit breakers and automatic failover for resilience.
How it works
1/2System architecture — multi-protocol ingestion, normalization, and fan-out to trading strategy engines
Tech Stack
What I'd do next
Migrate to a Rust-based ingestion layer for even lower latency on the hot path. Add machine learning-based anomaly detection on the data stream to flag potential market manipulation patterns before they impact trading decisions.