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

Create Java application

You can start by downloading the open-source libraries including 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.

It’s easy to get started with Amazon Kinesis Data Analytics Studio

Step 1: Create an Amazon Kinesis Data Analytics Studio application

Create Java application

You can start from the Amazon Kinesis Data Analytics, Amazon MSK, or Amazon Kinesis Data Streams console. You can also use custom connectors to connect to any other data source.

Java sample code

You can run individual paragraphs in the note, view results in context, and use Apache Zeppelin’s built-in visualization to accelerate development. You can also use user-defined functions in your code.

Step 3: Build and deploy as a Kinesis Data Analytics streaming application

Configure Java application

You can deploy your code as a continuously running stream processing application with a just few clicks. Your deployed application will be a Kinesis Data Analytics for Apache Flink application with durable state and autoscaling. You will also get the opportunity to change sources, destinations, logging, and monitoring levels before you productionize your code.

Get started with Amazon Kinesis Data Analytics 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 

E-Learning

Tutorial Workshop

In this workshop, you will build an end-to-end streaming architecture to ingest, analyze, and visualize streaming data in near real-time. You set out to improve the operations of a taxi company in New York City. You’ll analyze the telemetry data of a taxi fleet in New York City in near-real time to optimize their fleet operations.

Learn more »
Pre-Built Solution

AWS Streaming Data Solution for Amazon Kinesis

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.

Learn more »
Training Video

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.

Learn more »

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.