If I had to name a single piece of software that has impressed me lately, it would undoubtably be Redis. Not only is this key/value store on steroids blazing fast, but it is also very simple, and incredibly powerful.
How simple, you ask?
redis> SET mykey “Hello” OK redis> GET mykey “Hello”
It’s also a breeze to install and get up and running. The suggested way of installing Redis isn’t to fetch some pre-compiled package for your Linux distribution. It is to download the source code (a tiny 655K tarball) and build it yourself! This can be a real crap shoot for most software, but since Redis only depends on a working GCC compiler and libc, it is not an issue at all. It just works.
After it is installed, you can start it by simply running
at the command line. The quickstart guide also has some easy-to-follow instructions on how to start Redis automatically at boot as a daemon.
Redis is a very powerful piece of software. This power, I believe, is a direct result of its simplicity.
Redis is so much more than your run of the mill key/value store. In fact, calling it a key/value store would be like calling the Lamborghini Aventador a car. It would be far more accurate to call Redis a key/data structure store, because Redis natively supports hashes, lists, sets, and sorted sets as well. These data structures are all first class citizens in the Redis world. Redis provides a host of commands for directly manipulating the data in these data structures, covering pretty much any operation you would want to perform on a hash, list, set, or sorted set. Therefore, it is super simple to perform tasks like incrementing the value of a key in a hash by 1, push multiple values onto the end of a list, trim a list to the specified range, perform a union between two sets, or even return a range of members in a sorted set, by score, with scores ordered from high to low.
This native support for data structures, combined with Redis’ incredible performance, make it an excellent complement to a relational database. Every once in a while we’ll run into an issue where, despite our best efforts, our relational database simply isn’t cutting the mustard performance wise for a certain task. Time and time again, we’ve successfully been able to delegate these tasks to Redis.
Here are some examples of what we are currently using Redis for at Signal:
- Distributed locking. The SETNX command (set value of key if key does not exist) can be used as a locking primitive, and we use it to ensure that certain tasks are executed sequentially in our distributed system.
- Persistent counters. Redis, unlike memcache, can persist data to disk. This is important when dealing with counters or other values that can’t easily be pulled from another source, like the relational database.
- Reducing load on the relational database. Creative use of Redis and its data structures can help with operations that may be expensive for a relational database to handle on its own.
When Not To Use Redis
Redis stores everything in RAM. That’s one of the reasons why it is so fast. However, it is something you should keep in mind before deciding to store large amounts of data in Redis.
Redis is not a relational database. While it is certainly possible to store the keys of data as the values of other data, there is nothing to ensure the integrity of this data (what a foreign key would do in a relational database). There is also no way to search for data other than by key. Again, while it is possible to build and maintain your own indexes, Redis will not do this for you. So, if you’re looking to store relational data, you should probably stick with a relational database.
It is very clear that the Redis team has put a ton of effort into making sure that Redis remains simple, and they have done an amazing job.
It’s worth pointing out that Redis has some of the best online documentation that I have ever seen. All commands are easy to find, clearly documented, with examples and common patters of usage. AND the examples are interactive! Not sure what the result of a certain command will be? No need to install Redis and fire it up locally. You can simply try it right there in the browser.
With client libraries in virtually every programming language, there is no reason not to give it a try. You’ll be glad you did.