Amazon Kinesis Data Analytics

Get actionable insights from streaming data in real-time

Amazon Kinesis Data Analytics is the easiest way to analyze streaming data, gain actionable insights, and respond to your business and customer needs in real time. Amazon Kinesis Data Analytics reduces the complexity of building, managing, and integrating streaming applications with other AWS services. SQL users can easily query streaming data or build entire streaming applications using templates and an interactive SQL editor. Java developers can quickly build sophisticated streaming applications using open source Java libraries and AWS integrations to transform and analyze data in real-time.

Amazon Kinesis Data Analytics takes care of everything required to run your real-time applications continuously and scales automatically to match the volume and throughput of your incoming data. With Amazon Kinesis Data Analytics, you only pay for the resources your streaming applications consume. There is no minimum fee or setup cost.

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Powerful real-time processing

Amazon Kinesis Data Analytics provides built-in functions to filter, aggregate, and transform streaming data for advanced analytics. It processes streaming data with sub-second latencies, enabling you to analyze and respond to incoming data and streaming events in real time.

No servers to manage

Amazon Kinesis Data Analytics is serverless; there are no servers to manage. It runs your streaming applications without requiring you to provision or manage any infrastructure. Amazon Kinesis Data Analytics automatically scales the infrastructure up and down as required to run your applications with low latency.

Pay only for what you use

With Amazon Kinesis Data Analytics, you pay only for the processing resources that your streaming applications use. There are no minimum fees or upfront commitments.

Easy to use

Amazon Kinesis Data Analytics enables you to easily and quickly build queries and sophisticated streaming applications in three simple steps: setup your streaming data sources, write your queries or streaming applications, and setup your destination for processed data. Amazon Kinesis Data Analytics takes care of running your queries and applications continuously on data while it’s in transit and sending the results to your destinations.


Amazon Kinesis Data Analytics provides templates and an interactive editor that enable you to build SQL queries that perform joins, aggregations over time windows, filters, and more. You simply select the template appropriate for your analytics task, and then edit the provided code using the SQL editor to customize it for your specific use case.


Amazon Kinesis Data Analytics includes open source libraries based on Apache Flink that enable you to build an application in hours instead of months. Using your favorite IDE, you can connect to AWS and install the Java libraries. The extensible libraries include more than 25 pre-built operators to filter, aggregate, and transform streaming data, and integrations with AWS services like Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Kinesis Data Streams, Amazon Kinesis Data Firehose, Amazon Elasticsearch Service, Amazon S3, and Amazon DynamoDB.

How it works

How Amazon Kinesis Data Analytics works

Use cases

Amazon Kinesis Data Analytics is ideal for solving a wide range of streaming data use cases, including:

Streaming ETL for Internet-of-Things (IoT) with Java applications

You can write Java applications and use Amazon Kinesis Data Analytics to transform, aggregate, and filter streaming data from IoT devices such as consumer appliances, embedded sensors, and TV set-top boxes. You can then use the data to send real-time alerts when a sensor exceeds certain operating thresholds.

Watch how John Deere extracts IoT sensor measurements from agricultural equipment, transforms them into useful customer information in real time, and loads the transformed data into a data lake. 

Streaming ETL for IoT

Real-time log analytics with SQL

You can stream billions of small messages to Amazon Kinesis Data Analytics and calculate key metrics, which you can then use to refresh content performance dashboards in real time and improve content performance. Check out our real-time log monitoring solution brief.

Real-time log analytics with SQL

Ad tech and digital marketing with SQL

You can ingest different types of data records from audience tracking systems, ad exchange listeners/bidders, and ad servers, and combine them into the same stream. Then, you can use Amazon Kinesis Data Analytics to perform data transformations continuously to power real-time advertising and digital marketing solutions. Learn more from our real-time web analytics solution brief.

Ad tech and digital marketing with SQL


Autodesk case study
Autodesk computes real-time monitoring metrics such as response time and error-rate spikes for monitoring user experience.
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Real-time event sorting and filtering.
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Event prioritization and filtering to downstream applications.
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Zynga analyzes real-time game events triggered by player actions at scale.
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Yieldmo case study
Yieldmo analyzes online ad-interaction data in milliseconds.
Read case study 
Palringo case study
Palringo increases user engagement for its mobile community gaming app using real-time metrics.
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Gunosy blog post
Gunosy processes 500,000+ records per minute for fast, personalized news curating for end users.
Read blog post 

Get started with Amazon Kinesis Data Analytics

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

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