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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
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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

Creating operational insights using SQL Engine

Streaming SQL builds on the concepts of Structured Query Language (SQL) commonly used in various relational databases. Building on top of SQL means that SQL streaming generally has a lower learning curve for those familiar with databases. While there is no standard streaming SQL syntax, KDA uses the ANSI 2008 SQL standard with extensions that allow us to create real-time stream processing solutions. The key difference compared with the SQL database is that streaming SQL operates on a continuous data flow (stream). The following are the crucial advantages of streaming SQL:

  • It's easy to learn for those who have worked with a SQL database.
  • Its behavior is well understood as it uses the concepts of tables, joins, and aggregate functions.
  • There is a rich ecosystem of SQL tools and code generators.

If you are thinking, "this is great, I'm going to replace my database," that's not the case...

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