implementing-query-caching

Implement Redis query caching for Prisma 6 with TTL-based invalidation.

Updated Nov 21, 2025

Search Tags:#redis #cache #prisma #ttl

Ready to run

npx skills add https://github.com/djankies/claude-configs --skill implementing-query-caching

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: implementing-query-caching
Source: https://github.com/djankies/claude-configs/tree/main/prisma-6/skills/implementing-query-caching
Command: npx skills add https://github.com/djankies/claude-configs --skill implementing-query-caching

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill guides implementing a caching layer for Prisma queries using Redis, including cache key design, invalidation, and TTL strategies.

Core Features & Use Cases

Cache Layer: Wrap Prisma queries with a Redis cache.
Invalidation: Invalidate on mutations to keep data fresh.
TTL Tuning: Different TTLs per data type for performance.

Quick Start

Introduce a cache wrapper around a read query, store results in Redis, and invalidate on write.

Frequently Asked Questions about implementing-query-caching

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I add caching to Prisma queries with Redis?▼

Implement query caching by wrapping Prisma read operations with a Redis cache layer using a cache-aside pattern: check Redis first, return cached data if present, otherwise query Prisma and store the result with a TTL before returning. This reduces database load on frequently accessed or slow queries.

How do I invalidate cached Prisma query results when data changes?▼

Invalidate cache entries on mutations by deleting or updating Redis keys when Prisma write operations (create, update, delete) occur. Tie invalidation logic directly to your mutation handlers to keep cached data consistent with the database.

Can I use different cache expiration times for different data types?▼

Yes, configure per-type TTL settings in your cache layer so frequently-changing data expires quickly while stable data persists longer. Assign appropriate TTLs based on how often each entity type is read and how quickly stale data becomes problematic.

What happens to my queries if Redis becomes unavailable?▼

Implement robust fallback handling to query Prisma directly when Redis is unreachable or fails. This ensures your application continues functioning in degraded mode rather than failing entirely, though you lose caching benefits temporarily.

Do I need deterministic cache keys for Prisma queries?▼

Yes, generate consistent cache keys from query parameters so the same query always produces the same key. Deterministic keys enable reliable invalidation and prevent duplicate cache entries for identical queries.

Is query caching suitable for high-traffic Prisma applications?▼

Query caching is ideal for read-heavy, high-traffic workloads where repeated queries to the same data dominate. It significantly reduces database calls and latency, making it effective for scaling applications with hot data access patterns.