This is a modern cache implementation, inspired by the SIEVE is Simpler than LRU: an Efficient Turn-Key Eviction Algorithm for Web Caches (NSDI'24) paper. It offers state-of-the-art efficiency and scalability compared to other LRU-based cache algorithms.

Based on the Go implementation (JS implementation is without mutex). All credits to @scalalang2.

Basic Usage

import { Sieve } from 'js-sieve';

const cache = new Sieve<string, string>(1000);
cache.set("hello", "world")
const [v, _] = cache.get("hello");
console.log(v) // => "world"

Benchmark

The benchmark result were obtained using go-cache-benchmark, all credits to golang-fifo:

itemSize=500000, workloads=7500000, cacheSize=0.10%, zipf's alpha=0.99, concurrency=16

      CACHE      | HITRATE | MEMORY  |   QPS   |  HITS   | MISSES
-----------------+---------+---------+---------+---------+----------
  sieve          | 47.66%  | 0.09MiB | 2508361 | 3574212 | 3925788
  tinylfu        | 47.37%  | 0.11MiB | 2269542 | 3552921 | 3947079
  s3-fifo        | 47.17%  | 0.18MiB | 1651619 | 3538121 | 3961879
  slru           | 46.49%  | 0.11MiB | 2201350 | 3486476 | 4013524
  s4lru          | 46.09%  | 0.12MiB | 2484266 | 3456682 | 4043318
  two-queue      | 45.49%  | 0.17MiB | 1713502 | 3411800 | 4088200
  clock          | 37.34%  | 0.10MiB | 2370417 | 2800750 | 4699250
  lru-groupcache | 36.59%  | 0.11MiB | 2206841 | 2743894 | 4756106
  lru-hashicorp  | 36.57%  | 0.08MiB | 2055358 | 2743000 | 4757000

For additional info about SIEVE, head to golang-fifo. You'll find explanations why SIEVE is so good, why you should use it instead of FIFO/LRU, and things to consider before using it.

Contribution

How to run tests

$ npx esno test/index.mts

How to run benchmark test

$ npx esno bench/index.mts