But should you choose to back up the data, you will decide if you want to dump the dataset to the disk, or if you would rather append commands to a disk-based log. If you choose not to you will still have the networked, in-memory cache. Because Redis is in-memory, you must consider whether you want to backup, or “persist”, the data. Redis also allows you to run atomic operations, such as incrementing the value in a hash or even pushing an element in a list.
Redis also has transactions, different levels of on-disk persistence, and built-in replication. It has the advantages and capabilities of NoSQL databases. This means it allows data structures like strings, hashes, lists, sets, sorted sets of data, bit maps, and so on. The storage structure is both open-source and in-memory. Redis is a data structure store that can be used as a database, cache, or even a message broker. Then, we can compare some of the overall differences between MySQL and Redis. So, in our typical MySQL vs format, let’s first look at more into what Redis is, and a small background on that. For now, Redis will be that database we learn more about. But I was curious to learn more of the specifics, or at least pick up some more knowledge on Redis. For example, the only real background knowledge I do have about Redis is that it’s a NoSQL database. Just the name and some general information. I have heard about it, but only ever in passing. Admittedly, Redis was another resource I hadn’t heard about before. I’ve compared MySQL to a lot of other popular databases already but looking at the top ten I still haven’t covered Redis. Needing a change of pace, I decided to take a trip back to the MySQL versus series.
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