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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

Introducing GraphQL – what, when, and why

In this section, we will explore what GraphQL is. According to graphql.org, the official definition of GraphQL is that “GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.” Let’s dive a bit deeper to understand GraphQL.

Representational State Transfer (REST) has been the standard way of publishing data across systems, which is platform, device, and tool/language-agnostic. However, there are two major bottlenecks with REST:

  • For fetching different related entities, we need multiple REST requests. We must also be mindful of different versions of the API. Having different endpoints and their versions for each entity of functionality is a maintenance headache.
  • The request and response parameters are always fixed in REST. For example, there is a REST API that returns 100 fields. Suppose there is a consumer who only needs 10 fields. However, since responses...
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