Book Image

Scalable Data Architecture with Java

By : Sinchan Banerjee
Book Image

Scalable Data Architecture with Java

By: Sinchan Banerjee

Overview of this book

Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data. This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert. You’ll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you’ll understand how to architect a batch and real-time data processing pipeline. You’ll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you’ll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics. By the end of this book, you’ll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.
Table of Contents (19 chapters)
1
Section 1 – Foundation of Data Systems
5
Section 2 – Building Data Processing Pipelines
11
Section 3 – Enabling Data as a Service
14
Section 4 – Choosing Suitable Data Architecture

Data Storage and Databases

In the previous chapter, we understood the foundations of modern data engineering and what architects are supposed to do. We also covered how data is growing at an exponential rate. However, to make use of that data, we need to understand how to store it efficiently and effectively.

In this chapter, we will focus on learning how to store data. We will start by learning about various types of data and the various formats of the available data. We will briefly discuss encoding and compression and how well they work with various data types. Then, we will learn about file and object storage and compare these data storage techniques. After that, we will cover the various kinds of databases that are available in modern data engineering. We will briefly discuss the techniques and tricks to choose the correct database for a particular use case. However, choosing the correct database doesn’t guarantee a well-built solution. As a data architect, it is important...