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

Summary


In this chapter, we looked at an in-depth design of a data-collection system that we want to build from scratch. There are times when this is a good approach, mostly when your data-collection needs are simple and well-defined.

There are also times when you would not want to implement a homegrown solution, but rather look at tools that may already be available. This may be due to many reasons. For example, a shortage on engineering staff, a fast turnaround, a buy-over-build policy, and so on.

If you fall into the second category, stay tuned, as the next chapter discusses some of the tools that are available in the market for collecting and normalizing data.