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Amazon DynamoDB - The Definitive Guide

You're reading from   Amazon DynamoDB - The Definitive Guide Explore enterprise-ready, serverless NoSQL with predictable, scalable performance

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781803246895
Length 414 pages
Edition 1st Edition
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Author (1):
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Aman Dhingra Aman Dhingra
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Aman Dhingra
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Table of Contents (24) Chapters Close

Preface 1. Part 1:Introduction and Setup
2. Chapter 1: Amazon DynamoDB in Action FREE CHAPTER 3. Chapter 2: The AWS Management Console and SDKs 4. Chapter 3: NoSQL Workbench for DynamoDB 5. Part 2: Core Data Modeling
6. Chapter 4: Simple Key-Value 7. Chapter 5: Moving from a Relational Mindset 8. Chapter 6: Read Consistency, Operations, and Transactions 9. Chapter 7: Vertical Partitioning 10. Chapter 8: Secondary Indexes 11. Part 3: Table Management and Internal Architecture
12. Chapter 9: Capacity Modes and Table Classes 13. Chapter 10: Request Routers, Storage Nodes, and Other Core Components 14. Part 4: Advanced Data Management and Caching
15. Chapter 11: Backup, Restore, and More 16. Chapter 12: Streams and TTL 17. Chapter 13: Global Tables 18. Chapter 14: DynamoDB Accelerator (DAX) and Caching with DynamoDB 19. Part 5: Analytical Use Cases and Migrations
20. Chapter 15: Enhanced Analytical Patterns 21. Chapter 16: Migrations 22. Index 23. Other Books You May Enjoy

Summary

In this chapter, we expanded our understanding of NoSQL, emphasizing the distinctive design patterns between RDBMS and NoSQL, with a specific focus on DynamoDB. We explored strategies such as duplication and denormalization, which optimize for compute over storage. This approach minimizes expensive runtime joins and prioritizes efficient data retrieval.

While discussing denormalization, we delved into strategies for efficient data modeling in DynamoDB. We highlighted scenarios favoring a single DynamoDB table for related entities versus multiple tables, emphasizing that there is no one-size-fits-all approach. Sometimes, segregating data into separate DynamoDB tables proves more efficient.

Furthermore, we examined the intricacies of breaking down data in NoSQL databases, emphasizing smart partitioning strategies. This section also covered handling LOBs in DynamoDB, detailing strategies based on factors such as latency, update frequency, and application dependencies.

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