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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

Future growth and expansion

In the realm of NoSQL systems, a well-recognized and widely accepted trade-off involves sacrificing query flexibility to achieve predictable performance and high scalability. While the horizontal scaling of NoSQL databases can deliver exceptional performance at scale, they are not optimized to seamlessly support read queries with numerous optional and unknown filters. Furthermore, in the context of databases such as DynamoDB, the requirement to have knowledge of 60-70% of your application’s access patterns upfront may prove to add an additional layer of complexity for users.

For tables implementing non-overloaded partition key and sort key attribute names instead of the generic PK and SK, evolving the table schema may be an involved process. This evolution may require creating a new table with the evolved key schema and migrating data from the current table, often involving varying degrees of downtime requirements. This highlights a significant...

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