Designing highly performant architectural solutions often requires the use of caches.
In today's content we are going to talk about caches in particular about Redis, also addressing the differences between relational databases and NOSQL.
We will also illustrate some architectural suggestions making use of caches.
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Redis is an open source (BSD licensed) in-memory data structure repository used as a database, cache, and message broker.
In addition to being easy to use, it supports several types of frameworks that allow the developer to meet the vast majority of data needs that a problem may require.
It stores information in key-value style and supports complex value types, which makes it possible to use the technology in many types of cases. In addition, Redis has strategies to store data in memory and on disk, ensuring fast response and data persistence.
The supported value types that are most commonly used are:
String;
lists;
HashMap;
Sep.
Note that the ability to use HashMap makes virtually any serializable data object capable of being stored in Redis.
The other supported data types are equally useful and can be used in more specific or simpler cases.
Every value is accompanied by a key, which is used to retrieve the stored values and makes it possible to configure expiration rules, making Redis work as a kind of cache for that data.
Redis does not have the concept of schemas like other databases, so it is necessary to make key definitions that allow a logical separation of each of the types of data stored.
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