Summary

Any software application relies heavily on its database, so it’s important to give it the attention it deserves. In this chapter, we explored the interesting history of data storage, from its early days to the modern era of cloud computing. Throughout this journey, we witnessed the impacts of data storage evolution on the field of software engineering, and how Java frameworks have also evolved to be able to support polyglot solutions. As experienced software engineers, it is crucial for us to understand the importance of data and solutions that can manage and manipulate it effectively.

Adding to that, we discussed the challenges of relational databases, such as data redundancy and normalization, and how NoSQL databases emerged to handle unstructured data needs. We introduced the CAP theorem and mentioned additional studies, such as PACELC, to explain the challenges of implementing distributed data storage solutions.

As we continue through this book, we’ll delve deeper into the advanced architectural and development practices, challenges, and trade-offs you must know about in order to deliver the optimal persistence layer for each solution you get to work with from now on, related to data persistence. After taking a look at the history, motivation, and relationship between databases and Java, get ready to explore, in the next chapter, the different types of databases and their pros and cons.