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

Understanding file, block, and object storage

In this section, we will cover the various data storage formats that are essential for an architect who is planning to store their data. Data storage formats organize, keep, and present data in different ways, each with its pros and cons. The available data storage formats are file, block, and object.

File storage organizes and exposes data as a hierarchy of files and folders, whereas block storage divides the data into chunks and stores them in organized, evenly sized volumes. Finally, object storage manages the data in a space-optimized fashion and links it to its associated metadata.

Now, let’s dive deeper by discussing their basic concepts, pros and cons, and the use cases where they are applied. Let’s begin by discussing the simplest and the oldest of them all: file storage.

File storage

In file-level storage, data is stored as a single piece of information inside a file. This file is given a name, can contain...