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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KDS integration

The other streaming option for DynamoDB tables is native integration with KDS. The same kind of stream records that are generated in DynamoDB Streams are encapsulated with Kinesis-specific metadata and made available in a Kinesis data stream when opting to use KDS for your DynamoDB table. The motivation behind supporting KDS integration for DynamoDB was to allow users to effortlessly connect their DynamoDB tables to the Kinesis suite of services. The Kinesis suite includes KDS for your stream processing workloads, Kinesis Firehose Delivery Stream for aggregating and batch loading of streaming data into various other downstream services such as an S3 bucket or an OpenSearch domain, among others, and finally Kinesis Data Analytics for enhanced analytical capabilities on the streaming data.

Like DynamoDB Streams, KDS can record any mutations that happen on its associated DynamoDB table. Unlike DynamoDB Streams, KDS needs to be created and managed by the user separately...