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Scalable Data Architecture with Java

You're reading from   Scalable Data Architecture with Java Build efficient enterprise-grade data architecting solutions using Java

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781801073080
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Sinchan Banerjee Sinchan Banerjee
Author Profile Icon Sinchan Banerjee
Sinchan Banerjee
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1 – Foundation of Data Systems
2. Chapter 1: Basics of Modern Data Architecture FREE CHAPTER 3. Chapter 2: Data Storage and Databases 4. Chapter 3: Identifying the Right Data Platform 5. Section 2 – Building Data Processing Pipelines
6. Chapter 4: ETL Data Load – A Batch-Based Solution to Ingesting Data in a Data Warehouse 7. Chapter 5: Architecting a Batch Processing Pipeline 8. Chapter 6: Architecting a Real-Time Processing Pipeline 9. Chapter 7: Core Architectural Design Patterns 10. Chapter 8: Enabling Data Security and Governance 11. Section 3 – Enabling Data as a Service
12. Chapter 9: Exposing MongoDB Data as a Service 13. Chapter 10: Federated and Scalable DaaS with GraphQL 14. Section 4 – Choosing Suitable Data Architecture
15. Chapter 11: Measuring Performance and Benchmarking Your Applications 16. Chapter 12: Evaluating, Recommending, and Presenting Your Solutions 17. Index 18. Other Books You May Enjoy

A practical use case – exposing federated data models using GraphQL

In this section, we will learn how to develop DaaS using GraphQL in Java. To implement the solution, we will publish the same set of APIs that we published earlier using REST, but this time, we will implement the solution using GraphQL.

Before we start implementing GraphQL, it is important to design the GraphQL schema for our use case. In our use case, we need to read credit card applications from MongoDB using either the application ID or consumer ID. This was why we needed two separate endpoints in the REST-based solution (please refer to Chapter 9, Exposing MongoDB Data as a Service, for the REST-based DaaS solution).

Let’s analyze the requirements from a different perspective – that is, while considering the GraphQL-based solution. The biggest difference that GraphQL makes is that it reduces the number of endpoints, as well as the number of calls. So, for our use case, we will have a...

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