Amazon Kinesis Data Analytics is the easiest way to process and analyze streaming data in real-time with ANSI standard SQL. It enables you to read data from Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose, and build stream processing queries or entire applications using SQL to filter, transform, and aggregate the data continuously as it arrives. Amazon Kinesis Data Analytics automatically recognizes standard data formats, parses the data, and suggests a schema, which you can edit using the interactive schema editor. It provides an interactive SQL editor and stream processing templates so you can build sophisticated stream processing applications in just minutes. Amazon Kinesis Data Analytics runs the queries in your streaming applications continuously, and writes the processed results to output destinations such as Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose, which can deliver the data to Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service. Amazon Kinesis Data Analytics automatically provisions, deploys, and scales the resources required to run your streaming applications.

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Amazon Kinesis Data Analytics elastically scales up and down to match the data throughput. You only pay for the resources used to run your streaming applications. You need not worry about provisioning infrastructure or pay for idle capacity.

Amazon Kinesis Data Analytics delivers sub 1-second processing latencies so you can generate real-time alerts, dashboards, and actionable insights.

Amazon Kinesis Data Analytics integrates with Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose so that you can readily ingest streaming data. Just point Amazon Kinesis Data Analytics at the input stream and it will automatically read and parse the data, and make it available for processing. You can emit processed results to other AWS services including Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service through Amazon Kinesis Data Firehose. You can also send output data to Amazon Kinesis Data Streams to build advanced stream processing pipelines.

Amazon Kinesis Data Analytics provides an easy-to-use schema editor to discover and edit the structure of the input data. The wizard automatically recognizes standard data formats such as JSON and CSV, it then infers the structure of the input data to create a baseline schema, which you can further refine using the schema editor.

Amazon Kinesis Data Analytics provides an interactive editor to build SQL queries using streaming data operations like sliding time-window averages. You can also view streaming results and errors using live data to debug or further refine your script interactively.

Amazon Kinesis Data Analytics supports standard ANSI SQL so all you need is familiarity with SQL.

The interactive SQL editor comes bundled with a collection of stream processing templates that provide baseline SQL code for the most common types of operations such as aggregation, per-event transformation, and filtering. 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 offers functions optimized for stream processing so that you can easily perform advanced analytics such as anomaly detection and top-K analysis on your streaming data.