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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

Amazon Kinesis Data Analytics (KDA)

Amazon KDA was launched in August 2016. KDA is a fully managed, serverless service for continuously processing real-time streaming data. When it launched in August 2016, it supported the SQL engine, allowing users to query continuously streaming data and get insights from the data in real time without learning a new API or a new programming language. KDA supports ANSI SQL standard with extensions. Later, in November 2018, Amazon KDA launched the second supported underlying real-time processing engine in Apache Flink. It is now called Amazon Kinesis Data Analytics for Apache Flink. As the name suggests, it offers the popular, open source, highly parallel, and low-latency distributed processing framework for stateful computations Apache Flink as a fully managed serverless service. In terms of the five core stages of enabling real-time analytics, Amazon KDA falls in the real-time stream processing stage.

Amazon KDA for SQL

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