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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

Core Architectural Design Patterns

In the previous chapters, we learned how to architect data engineering solutions for both batch-based and real-time processing using specific use cases. However, we haven’t discussed the various options available concerning architectural design patterns for batch and real-time stream processing engines.

In this chapter, we will learn about a few commonly used architectural patterns for data engineering problems. We will start by learning about a few common patterns in batch-based data processing and common scenarios where they are used. Then, we will learn about various streaming-based processing patterns in modern data architectures and how they can help solve business problems. We will also discuss the two famous hybrid data architectural patterns. Finally, we will learn about various serverless data ingestion patterns commonly used in the cloud.

In this chapter, we will cover the following topics:

  • Core batch processing patterns...
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