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

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781803246895

Length 414 pages

Edition 1st Edition

Languages

Java

Tools

AWS

Concepts

Databases

Author (1):

Aman Dhingra

View More author details

Table of Contents (24) Chapters

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

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Diving into analytical patterns

In this section, we will explore different architectural patterns and their use cases for analytics on DynamoDB data. We will also discuss the advantages and considerations of each pattern, depending on specific requirements. Before diving into the patterns themselves, let us review some of the building blocks these patterns may use.

Building blocks

The following building blocks are leveraged by analytical patterns to achieve their goals. These include native DynamoDB features, other AWS services, and architectural patterns that integrate well with DynamoDB, ensuring scalability, high availability, and adherence to well-architected pillars (9).

Full table scans

While not recommended for serving OLTP requests from tables with large volumes of data, full table scans can be a straightforward way to support analytics on DynamoDB data without the need for complex workflows and analytical data pipelines. You can perform full table scans using the...