#Data Structures & Algorithms

• LRU Cache: From Classic Implementation to Modern Alternatives

  16 min read • Published on March 21, 2023

  Caching is the unsung hero of high-performance applications. When implemented correctly, it can dramatically reduce latency, ease database load, and create a snappy, responsive user experience. Statistics show that even a one-second delay can cut conversions by 7%. For decades, the go-to solution for developers has been the Least Recently Used (LRU) cache, a simple yet effective strategy for keeping frequently used data close at hand.But what happens when this trusty tool fails? While LRU is a powerful default, it has a critical flaw that can cripple performance under common workloads. This vulnerability has spurred decades of research, leading to a new generation of smarter, more resilient caching algorithms that build upon LRU’s foundation.This guide will take you on a journey from the classic LRU cache implementation to understanding its limitations and exploring modern alternatives. We’ll dive deep into LRU’s inner workings, examine when it fails, and discover how advanced algorithms like LRU-K, 2Q, and ARC address these shortcomings.