Learning redis from the bottom
What does Redis actually mean?
It means REmote DIctionary Server.
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions, and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
You 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.
To achieve top performance, Redis works with an in-memory dataset. Depending on your use case, you can persist your data either by periodically dumping the dataset to disk or by appending each command to a disk-based log. You can also disable persistence if you just need a feature-rich, networked, in-memory cache.
Redis also supports asynchronous replication, with very fast non-blocking first synchronization, auto-reconnection with partial resynchronization on net split.
Other features include:
- Lua scripting
- Keys with a limited time-to-live
- LRU eviction of keys
- Automatic failover
You can use Redis from most programming languages.
Redis is written in ANSI C and works in most POSIX systems like Linux, *BSD, and OS X, without external dependencies. Linux and OS X are the two operating systems where Redis is developed and tested the most, and we recommend using Linux for deployment. Redis may work in Solaris-derived systems like SmartOS, but the support is best effort. There is no official support for Windows builds.
How does Redis work?
All Redis data resides in-memory, in contrast to databases that store data on disk or SSDs. By eliminating the need to access disks, in-memory data stores such as Redis avoid seek time delays and can access data in microseconds. Redis features versatile data structures, high availability, geospatial, Lua scripting, transactions, on-disk persistence, and cluster support making it simpler to build real-time internet scale apps.
Who's using Redis?
A list of well known companies using Redis:
Popular Redis Use Cases
- Chat, messaging, and queues
- Gaming leaderboards
- Session store
- Rich media streaming
- Machine learning
- Real-time analytics
Why is Redis different compared to other key-value stores?
There are two main reasons.
- Redis is a different evolution path in the key-value DBs where values can contain more complex data types, with atomic operations defined on those data types. Redis data types are closely related to fundamental data structures and are exposed to the programmer as such, without additional abstraction layers.
- Redis is an in-memory but persistent on disk database, so it represents a different trade off where very high write and read speed is achieved with the limitation of data sets that can’t be larger than memory. Another advantage of in memory databases is that the memory representation of complex data structures is much simpler to manipulate compared to the same data structures on disk, so Redis can do a lot, with little internal complexity. At the same time the two on-disk storage formats (RDB and AOF) don’t need to be suitable for random access, so they are compact and always generated in an append-only fashion (Even the AOF log rotation is an append-only operation, since the new version is generated from the copy of data in memory). However this design also involves different challenges compared to traditional on-disk stores. Being the main data representation on memory, Redis operations must be carefully handled to make sure there is always an updated version of the data set on disk.
Redis official interactive tutorial can be found here:
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