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

Introducing DaaS – what and why

In the introduction, we briefly discussed and established that DaaS is useful for publishing already-ingested and analyzed data securely.

But what is DaaS? It is a data management strategy that enables data as a business asset, which makes valuable and business-critical data accessible on demand to various internal and external systems. Software-as-a-Service (SaaS) started becoming popular in the late 90s when software was provided to consumers on demand. Similarly, DaaS enables access to data on demand. With the help of service-oriented architectures (SOAs) and APIs, it enables secure platform-independent data access. The following diagram provides an overview of a DaaS stack:

Figure 9.1 – DaaS stack overview

As we can see, data from different kinds of data stores, such as data warehouses, data lakes, or online databases, can be unified by a virtual data layer that can be used to build the services or API layer...