Suggest an editImprove this articleRefine the answer for “Why is Redis often used as a cache layer?”. Your changes go to moderation before they’re published.Approval requiredContentWhat you’re changing🇺🇸EN🇺🇦UAPreviewTitle (EN)Short answer (EN)Redis is often used as a cache layer because storing data in RAM gives access in microseconds, the "key-value" model gives O(1) reads, and TTL plus eviction algorithms (LRU) automatically keep the cache fresh and "hot". **Key point:** caching drastically cuts down calls to the main DB - if the data is already in Redis, it's returned immediately (a cache hit); if not, it's fetched from the DB, stored in Redis, and returned to the user (a cache miss).Shown above the full answer for quick recall.Answer (EN)ImageRedis is often used as a **cache layer**, because it's a great fit for **speeding up access to frequently used data** without loading down the main database. ### 1. Storing data in RAM Redis is an **in-memory** database, everything lives in **RAM**, and accessing RAM is thousands of times faster than accessing disk. *The result:* data comes back from Redis in **microseconds**, while an SQL query might take milliseconds or seconds. ### 2. The "key-value" model, instant access Redis is built simply: every item is stored by a **key**. There's no need to parse complex queries or build indexes. *The result:* fetching data (GET) happens in **O(1)**, instantly, even with millions of records. ### 3. TTL support (time to live) Any key can be given an **expiration time (Time To Live)**. Once the TTL runs out, Redis removes the record automatically. *The result:* the cache "cleans itself", always staying current. ### 4. Reducing load on the main DB Caching in Redis sharply cuts the number of calls to the main database. Example: 1. The application looks for data in Redis. 2. If it's there → it's returned right away ("a cache hit"). 3. If not → it's fetched from the DB, saved into Redis, and returned to the user ("a cache miss"). *The result:* the main DB is freed from repeated queries. ### 5. Support for complex data structures Redis can store not just strings, but also lists, sets, hashes, JSON, and more. That means it can cache not just "answers" but also complex structures, profiles, feeds, filters. ### 6. Minimal latency and high throughput Redis can handle **hundreds of thousands of requests per second** with sub-1ms latency. That's why it fits even high-load systems (Instagram, Twitch, GitHub). ### 7. TTL + LRU = a smart cache Redis supports **eviction algorithms**, e.g. **LRU (Least Recently Used)**. When memory runs low, it automatically removes the least-used data. *The result:* the cache always holds only "hot" data. **Summary:** Redis is used as a cache layer because it: - stores data in **RAM** (maximum speed), - supports **TTL and LRU**, - integrates easily with any application, - takes load off the main database. In short: Redis = a "fast layer" between an application and slower storage.For the reviewerNote to the moderator (optional)Visible only to the moderator. Helps review go faster.