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. 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.
It's easy to get started
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.
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.
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.
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.
This Developer Guide gives you an overview of the Amazon Kinesis Data Analytics architecture, creating applications, and confuguring inputs and outputs.
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.
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: