Book Image

Architecting Data-Intensive Applications

By : Anuj Kumar
Book Image

Architecting Data-Intensive Applications

By: Anuj Kumar

Overview of this book

<p>Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet ?uent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture.</p> <p>This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn’t fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand.</p>
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Chapter 11. Let Us Store the Data

We are living in the age of data. It is everywhere. Everybody is generating it and everything is generating it. Twitter, Instagram, Facebook, IoT devices, Industrial IoT devices, sensors, gaming consoles, web applications, stock trading, you name it. And on top of that, things are also getting connected to each other. But the real question is, "Where do we store this data and how shall we store this data?" It is not a simple question to answer, as we will learn in this chapter.

In this chapter, we will discuss following topics:

  • The data explosion problem and how traditional relational systems were not meant for handling such huge amounts of data
  • Hadoop and why the industry is crazy about it
  • Columnar stores, the use cases they solve and why they are considered worthy of big data storage
  • Connected data and the graph stores that enable data to be represented as nodes and edges