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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The AWS Management Console and SDKs

Before we begin designing, building, and working with DynamoDB, we should understand what tools and options are available for us to interact and work with. Unlike some NoSQL databases that you connect directly to the primary server or host with (Redis or MongoDB, for example), DynamoDB is different—we interact with it through a series of stateless application programming interfaces (APIs).

The underlying service of those APIs corresponds to fleets of request routers and storage nodes, all of which take care of sending our requests to the correct storage nodes, managing any authentication and authorization alongside interfacing with any additional service features, such as point-in-time recovery (PITR) and read/write capacity modes.

Having most tasks abstracted away into an API means we can focus more on our application and data modeling. While, at first, querying a database through API calls may seem strange, it can really help with...