Redis
An in-memory data store used as a database, cache, and message broker.
Overview
Redis (REmote DIctionary Server) is an open source in-memory key-value database. It's often used as a cache, message broker, and for real-time analytics. Redis supports a variety of different data structures, including strings, hashes, lists, sets, and sorted sets. It also provides several key database features such as replication, persistence, and high availability. Overall, Redis is a powerful tool for building high-performance applications and it's a popular topic in system design.
Let's break down a couple of key terms before we begin:
- Key-value database: A type of database that stores data as a collection of key-value pairs, where each key is unique and maps to a specific value.
- In-memory: Data is stored in the main memory (RAM) of the server
- Persistence: The ability to save data to disk so that it can be recovered after a restart or crash.
- Replication: The process of copying data from one server (the master) to one or more other servers (the replicas) to ensure data availability and redundancy.
In many cases, Redis is used as a cache that sits in front of a primary database with the purpose of improving read performance. It can help reduce the load on the primary database by serving frequently accessed data from memory, which is much faster than disk-based storage.
Data Types
As opposed to Memcached, Redis supports a variety of data types. Each of them has it's own use cases and several serve to extend the functionality of Redis beyond a simple key-value store. You can consider Redis to be something like a dictionary, where the keys are strings but the values can be of different types. Different keys will store different values and the type of value can be different for each key.
| Type | Example Value |
|---|---|
| String | hello world |
| Hash | {a: "hello", b: "world"} |
| List | [A>B>C>C] |
| Set | {A<B<C} |
| Sorted Set | {A:1, B:2, C:3} |
| Stream | {id1=t1.seq(...)} |
| Bitmap | 0110110101101101 |
| Geo | {A: (50.1, 0.5)} |
| HyperLogLog | 01101101 01101111 |
Caching
The most common use of Redis is as a cache — a fast, in-memory layer that sits between your application and a slower persistent database like MySQL or PostgreSQL.
The idea is simple: before hitting the database for every read, check Redis first. If the data is there (a cache hit), return it immediately. If not (a cache miss), fetch it from the database, store it in Redis for next time, and then return it.
This pattern is sometimes called cache-aside (or lazy-loading) because the application is responsible for populating the cache on demand.
Step through each scenario below to see how data flows:
Client sends a request to the application server.