Introduction

Check this Redis cheat sheet https://quickref.me/redis.html .

Redis is an open-source in-memory data structure store written in C language and used as a database, cache, message broker, and streaming engine.

• Redis is written in ANSI C and works on most POSIX systems like Linux, *BSD, and Mac OS X, without external dependencies.
• Linux and OS X are the two operating systems where Redis is developed and tested the most, and its recommend using Linux for deployment.
• Redis may work in Solaris-derived systems like SmartOS, but support is best effort.
• There is no official support for Windows builds.

Redis clients are available for widely used programming languages such as JAVA, Python, NodeJS, PHP, Golang etc.

It’s a key-value store that functions as a data structure server.

Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

• One can run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing an element to a list; computing set intersection, union and difference; or getting the member with highest ranking in a sorted set.

Redis's popularity is as a database, a cache, and a message broker in modern cloud architecture and so is a popular choice for caching, session management, gaming, leader boards, real-time analytics, geospatial, ride-hailing, chat/messaging, media streaming, and pub/sub apps.

Most database storage occurs on disk or on SSDs. As such, database operations require a round trip to disk. In contrast in-memory data resides in the server’s RAM, is not subjected to the same constraints, provides sub-millisecond response times, and thus supports magnitudes more operations.

• To achieve top performance, Redis works with an in-memory dataset. Depending on your use case, Redis can persist your data either by periodically dumping the dataset to disk or by appending each command to a disk-based log.
• One can also disable persistence if you just need a feature-rich, networked, in-memory cache.

To give you a few examples of Redis memory footprint (all obtained using 64-bit instances):

• An empty instance uses ~ 3MB of memory.
• 1 Million small Keys -> String Value pairs use ~ 85MB of memory.
• 1 Million Keys -> Hash value, representing an object with 5 fields, use ~ 160 MB of memory.