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Scalable Data Streaming with Amazon Kinesis

You're reading from   Scalable Data Streaming with Amazon Kinesis Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800565401
Length 314 pages
Edition 1st Edition
Languages
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Authors (4):
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Rajeev Chakrabarti Rajeev Chakrabarti
Author Profile Icon Rajeev Chakrabarti
Rajeev Chakrabarti
Tarik Makota Tarik Makota
Author Profile Icon Tarik Makota
Tarik Makota
Brian Maguire Brian Maguire
Author Profile Icon Brian Maguire
Brian Maguire
Danny Gagne Danny Gagne
Author Profile Icon Danny Gagne
Danny Gagne
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Table of Contents (13) Chapters Close

Preface 1. Section 1: Introduction to Data Streaming and Amazon Kinesis
2. Chapter 1: What Are Data Streams? FREE CHAPTER 3. Chapter 2: Messaging and Data Streaming in AWS 4. Chapter 3: The SmartCity Bike-Sharing Service 5. Section 2: Deep Dive into Kinesis
6. Chapter 4: Kinesis Data Streams 7. Chapter 5: Kinesis Firehose 8. Chapter 6: Kinesis Data Analytics 9. Chapter 7: Amazon Kinesis Video Streams 10. Section 3: Integrations
11. Chapter 8: Kinesis Integrations 12. Other Books You May Enjoy

Understanding delivery stream destinations

Delivery stream destinations are where KDF has the ability to land or send the ingested data. This is how KDF packages stream storage, data processing, and delivery into one neat tool that requires no code. KDF supports a number of destinations, and the KDF service has been adding additional destinations over time. Now, let's take a detailed look at the supported destinations.

Amazon S3

The first—and most popular—destination is Amazon S3. S3 is a serverless object-storage service that is highly scalable, highly durable, and highly available, and provides industry-leading performance and security features. It is designed for 99.999999999% (or 11 9s) of durability and provides storage for almost any amount of data. It provides the ideal storage at an affordable price point for use cases such as a data lake, and hence is an ideal destination for KDF. The most popular use case for using KDF is to populate a data lake that...

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