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

Desired properties of a data-intensive system


Any system that needs to handle vast amounts of data efficiently has to possess certain basic properties. These properties feed into defining the architectural principles, assumptions, capabilities, and patterns of the data-intensive system.

Let's discuss some of the core properties that we can find in a data-intensive system:

  • Robust and fault-tolerant

Today's systems are distributed by nature. What that means is that different components of the system usually run on different machines and those machines could either be located together, or in an entirely different time zone.

One of the many, many reasons behind building such an architecture is so that each individual component can be executed on a much smaller piece of hardware, requiring far fewer resources to function. This being the era of commodity hardware, it means that these components usually run on commodity hardware. Given that commodity hardware is usually unreliable and can go down randomly...