Real-Time APIs Are Simpler Than You Think: Redis, Lua, and 4k Updates/sec
The article describes building a high-performance real-time API for crypto price data using Redis and Lua instead of complex distributed systems. By moving sorting and filtering logic from Python to Redis, the team reduced network overhead and improved efficiency. The system achieved 4k updates per second while maintaining simplicity and low latency.
- ▪The system ingested 3k–4k crypto price updates per second from exchange WebSocket streams.
- ▪Initial implementation used Python for sorting and filtering, which created network transfer bottlenecks.
- ▪Redis was used to store mutable market data and power leaderboards via sorted sets, improving performance.
- ▪Logic was shifted from Python to Redis using Lua scripts to minimize data transfer and enhance speed.
- ▪The solution avoided complex infrastructure like Kafka and stream processors by leveraging Redis for real-time queryability.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3773589) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Gauthamram Ravichandran Posted on May 16 Real-Time APIs Are Simpler Than You Think: Redis, Lua, and 4k Updates/sec #redis #lua #python #showdev 1. Intro — The Problem We Actually Had Building real-time systems is often presented as a distributed systems problem. Kafka, stream processors, event buses, fanout pipelines, multiple caches — the architecture diagrams usually become complicated very quickly. But the problem we were trying to solve was actually much simpler.
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