Cache and Redis: Why and How to Use

Imagine your application makes thousands of queries to the same database. All this traffic generates latency, CPU load, disk load, and increases costs. In such scenarios, cache comes in: an ultra-fast memory (RAM) layer that stores recent results to avoid repeated database queries. Instead of reading from disk (which can take tens or hundreds of milliseconds), the cache responds in microseconds. In practice, using cache allows the application to do much more "cheap" work in memory and very few expensive operations on the database. For example, imagine a gaming site with 1 million visits per second displaying results. Without cache, that would be 1 million SELECTs on SQL. With Redis configured with a short TTL (e.g., 3s), Redis would handle about 60 million queries per minute, and only ~30 SQL queries would be executed, resulting in a drastic reduction in load. In other words, with a cache you go from "1,000,000 expensive operations" to "1 expensive operation + 999,999 cheap RAM acces