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.

You can build sophisticated applications using Apache Flink. Apache Flink is an open source framework and engine for processing data streams. Your applications can transform and analyze data in real time, and integrate with other AWS services in as little as one line of code. You can also use an interactive SQL editor to easily query streaming data and build streaming applications. Simply point to a streaming data source like Amazon Kinesis Data Streams and use standard SQL to analyze your 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.

Benefits

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 includes open source libraries and runtimes based on Apache Flink that enable you to build an application in hours instead of months using your favorite IDE. The extensible libraries include different APIs that are specialized for different use cases including stateful stream processing, streaming ETL, and real-time analytics. You can use the libraries to integrate 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, Amazon DynamoDB, and more.

Use standard SQL for interactive queries

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. Without writing a single line of code, you can send your SQL results to other AWS services like AWS Lambda, Amazon Kinesis Data Streams, and Amazon Kinesis Data Firehose.

Use cases

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

You can develop applications with Apache Flink libraries 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.

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.