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Introduction to Understanding Big Data Scalability

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This introduction describes the goals of the Big Data Scalability four-volume series, focusing on the underlying growth of databases (the "data explosion") and providing some background into big data's relevance.
This chapter is from the book

Big Data Scalability is a comprehensive, four-part volume containing information on many facets of database performance and scalability. I have found through years of experience that in order to master any aspect of software, databases, or computer science, the most important thing is a solid foundation and understanding of the fundamental concepts. Once you have this knowledge, you can apply it to solve real-world problems with your own database tier.

This series is primarily focused on how to apply Big Data scalability to common application problems with the wide selection of DBMS engines available today. As such, it is less focused on pure analytics Big Data problems with engines like Apache Hadoop (there are many other books dedicated to that), and more directed toward taking advantage of Big Data scalability with popular DBMS engines used in enterprise and online applications.

What You Will Learn

This part of the series will cover the following critical topics for building a high-performance, scalable, and reliable database tier:

  • The primary causes of database performance issues
  • What Big Data is
  • Options for scaling your application
  • When and how to scale your database
  • The fundamentals of data distribution (database sharding)
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