Active Module: Redis Caching & TTL Engine

Redis Caching Engine

Benchmark the performance gap between raw MySQL database compilation and Redis key-value retrieval. Observe Cache Hit vs Miss cycles and clear the cached values on demand.

Interactive Benchmark

Latest Execution Status

Execution Latency

Status / Cache State

Sum of views calculated:
Cache TTL configuration:

Caching Mechanics

What is happening

When "Use Redis Cache" is pressed, Laravel checks Redis memory for the key. On a MISS, MySQL runs `SUM(views)` and writes the result to Redis. On a HIT, Redis returns the sum directly, bypassing MySQL entirely.

Why it matters

Executing calculations or fetching complex configurations on database disks under high concurrency saturates DB pool size. Caching aggregates lightens read pressure dramatically.

Expected Performance

MySQL sum scanning takes ~4-10ms. Redis cached RAM responses execute in sub-millisecond ranges (~0.2 - 0.9ms), giving a 10x-50x speed increase.

Trade-offs & Invalidation

Cached data becomes stale if source records change. Invalidation patterns like clearing cache on post creation (Cache invalidation) or short TTL timers are required to preserve coherence.