The best way to get started with Amazon Kinesis Data Analytics is to get hands-on experience by building a sample application. Simply go to the Amazon Kinesis Data Analytics console and create a new Amazon Kinesis Data Analytics application. Depending on whether you choose an Apache Flink- or SQL-based application, use the following steps:

To get started, create a Kinesis Data Analytics application that continuously reads and processes streaming data. Download the open source Apache Flink libraries using your favorite IDE, and then write your application code and test it with live streaming data. You can configure destinations where you want Kinesis Data Analytics to send the results.

You can get instructions on how to download the libraries and create your first application in the Amazon Kinesis Data Analytics for Apache Flink Developer Guide. Here you will also find the required components to run applications that use Apache Beam. You can find equivalent code in other languages that Apache Flink supports in the official Apache Flink documentation for the Apache Flink version you are using on Amazon Kinesis Data Analytics.

Step 1: Download the open source libraries into your favorite IDE

Create Java application

You can start by downloading the open source libraries that include the AWS SDK, Apache Flink, and connectors for AWS services. 

Java sample code

You write your Apache Flink application code using data streams and stream operators. Application data streams are the data structure you perform processing against using your application code. Data continuously flows from the sources into application data streams. One or more stream operators are used to define your processing on the application data streams.

Step 3: Upload your code to Kinesis Data Analytics

Configure Java application

Once built, upload your code to Amazon Kinesis Data Analytics and the service takes care of everything required to run your real-time applications continuously including scaling automatically to match the volume and throughput of your incoming data.

The Getting Started with Amazon Kinesis Data Analytics for Apache Flink Applications section of the Developer Guide provides a simple walkthrough of building your first application.

Use a pre-built solution to get started quickly

Use AWS Streaming Data Solution for Amazon Kinesis to help you solve for real-time streaming use cases like capturing high volume application logs, analyzing clickstream data, continuously delivering to a data lake, and more.

The 15-minute training video explains how you use Apache Flink applications in Amazon Kinesis Data Analytics to get more timely insights from your data.

It's easy to get started with SQL

To get started, create a new Amazon Kinesis Data Analytics application. Select the demo stream we provide as input, pick a template, and edit the SQL query. You can then view the results right there in the console or load the output into Amazon Elasticsearch Service and visualize using Kibana. Within a few minutes, you will be able to deploy a complete streaming data application.

Step 1: Configure input stream

Configure input stream

First, go to the Amazon Kinesis Data Analytics console and select a Kinesis data stream or Kinesis Data Firehose delivery stream as input. Amazon Kinesis Data Analytics ingests the data, automatically recognizes standard data formats, and suggests a schema. You can refine this schema, or if your input data is unstructured, you can define a new schema using our intuitive schema editor.

Read documentation 

Step 2: Write your SQL queries

Write your SQL queries

Next, write your SQL queries to process the streaming data using the Amazon Kinesis Data Analytics SQL editor and built-in templates, and test it with live streaming data.

Read documentation 

Step 3: Configure output stream

Configure output stream

Lastly, point to the destinations where you want the results loaded. Amazon Kinesis Data Analytics integrates out-of-box with Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose so it’s easy to send processed results to Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, or your own custom destination.

Read documentation 

Getting started examples

These resources provide example streaming data applications and step-by-step instructions so you can try them out and gain hands-on experience.

How it works

This SQL Developer Guide gives you an overview of the Amazon Kinesis Data Analytics architecture, creating applications, and configuring inputs and outputs.

Getting started

In the Getting Started guide, we step you through setting up an AWS Account, the Command Line Interface (AWS CLI), and creating your starter Amazon Kinesis Data Analytics application.

Example applications

This Example Applications guide provides code examples and step-by-step instructions to help you create Amazon Kinesis Data Analytics applications and test your results.

How-to videos

It's easy to get started with Kinesis Data Analytics. The how-to videos make it even easier by providing technical deep dives into common use cases and stream processing workflows. They also provide in-depth overviews of key features so you can get your job done. Follow the links below to watch the recordings:

Introduction to Amazon Kinesis Data Analytics (2:21)
Feed real-time dashboards (3:14)
Create real-time alarms (2:59)
Generating time series analytics (2:32)

Get started with Amazon Kinesis Data Analytics

Sign up for an AWS account
Sign up for an AWS account

Instantly get access to the AWS Free Tier.

Review the getting started guide
Review the getting-started guide

Learn how to use Amazon Kinesis Data Analytics in the step-by-step guide for SQL or Apache Flink.

Start building in the console
Start building streaming applications

Build your streaming application from the Amazon Kinesis Data Analytics console.