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

Reference architecture for a data-intensive system


This section will provide readers with a high-level component view-based reference architecture for a data-intensive system. The objective and the idea is to enable users to understand the major components that play an important part in a data-heavy system without diving deep. This is intentional, since without an understanding of the high-level components, the author believes that the reader may not be able to grasp the complete picture.

Component view

The following diagram depicts a 10,000 ft view of an architecture that is capable of handling vast amounts of data efficiently and effectively. I have marked it as View 1 because I want to provide readers with different views of the same reference architecture. I prefer to refer to such views as perspectives on the same architecture, but focused on slightly different aspects, according to the target audience.

The reference architecture in the following View 1 is designed for someone who is starting...