Query Caching Strategies

This walks you through multi-level caching with Redis, Memcached, and database-level strategies. You get patterns for cache invalidation (both event-based and time-based), TTL configuration, and cache warming on startup. The quick start shows a basic Redis implementation with PostgreSQL, and the reference guides cover specific database pairings plus LRU eviction strategies. Honestly, the value here is having the invalidation patterns laid out clearly, since that's usually where caching implementations get messy. Good fit if you're adding a cache layer to an existing system or trying to reduce database load on high-read workloads.

skills.sh installs: 465
GitHub stars: 379
last updated: Aug 21, 2026

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Install

$ npx -y skills add aj-geddes/useful-ai-prompts --skill query-caching-strategies --agent claude-code

Installs into .claude/skills of the current project.

Files

Overview

Implement multi-level caching strategies using Redis, Memcached, and database-level caching. Covers cache invalidation, TTL strategies, and cache warming patterns.

When to Use

Query result caching
High-read workload optimization
Reducing database load
Improving response time
Cache layer selection
Cache invalidation patterns
Distributed cache setup

Quick Start

Minimal working example:

// Node.js example with Redis
const redis = require("redis");
const client = redis.createClient({
  host: "localhost",
  port: 6379,
  db: 0,
});

// Get user with caching
async function getUser(userId) {
  const cacheKey = `user:${userId}`;

  // Check cache
  const cached = await client.get(cacheKey);
  if (cached) return JSON.parse(cached);

  // Query database
  const user = await db.query("SELECT * FROM users WHERE id = $1", [userId]);

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