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Scalable Data Streaming with Amazon Kinesis

Scalable Data Streaming with Amazon Kinesis

By : Makota, Brian Maguire, Gagne, Chakrabarti
5 (4)
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Scalable Data Streaming with Amazon Kinesis

Scalable Data Streaming with Amazon Kinesis

5 (4)
By: Makota, Brian Maguire, Gagne, Chakrabarti

Overview of this book

Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale. Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you’ll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk. By the end of this AWS book, you’ll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).
Table of Contents (13 chapters)
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1
Section 1: Introduction to Data Streaming and Amazon Kinesis
5
Section 2: Deep Dive into Kinesis
10
Section 3: Integrations

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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