The decision as to whether Redis is the correct choice for a new project or to solve a data problem you might be experiencing really depends on the nature of your data and what you're trying to accomplish with your project. Redis, unlike relational databases or NoSQL document stores, does not require you to structure your data first before using it. Redis provides a direct, more algorithmic manipulation of your data through the use of a variety of data structures such as lists, hashes, sets, and sorted sets. Even if Redis is not your final choice, the exercise of breaking down your data into these data structures will help deepen the context and the analysis of the issue that you're trying to solve. A detailed example of such experimentation was given while representing a legacy library standard called MARC in the basic Redis hashes, lists, sets, and sorted sets. We then briefly reviewed three popular design patterns for using Redis as a web cache, Redis as the backend for a gamer leaderboard, and Redis used as a publish/subscribe messaging system. We finish this chapter by illustrating some recent changes to Redis that expand the types of problems that Redis can be the primary data solution that in the past traditional SQL database or other NoSQL technologies may have been adopted instead.

In the next chapter, we are going to first examine Redis keys and the importance of organizing these keys with a Redis key schema generated either through a Redis object mapper or through manual documentation. Chapter 2 then introduces the Big O notation, followed by a systematic review of the basic Redis data structures and commands based on time complexity measures, Chapter 2 finishes with an introduction to some of the newer data structures and commands, including bitstrings and HyperLogLog.