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Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics - service, which simplifies the transformation and real-time analysis of streaming data by leveraging the power of Apache Flink.

Key definitions for Amazon Kinesis Data Analytics:

  • Open Source

    Amazon Kinesis Data Analytics offers seamless integration with a diverse range of open-source libraries, including Apache Flink, Apache Beam, Apache Zeppelin, and the AWS SDK. It also provides smooth integration with multiple AWS services. Apache Flink, in particular, acts as an open-source framework and engine specifically designed for developing dependable and accurate streaming applications. Apache Beam offers a unified model for defining both streaming and batch data processing applications that can be executed across multiple execution engines. The AWS software development kits (SDKs) simplify coding for numerous AWS services by providing language-specific APIs, along with AWS libraries, code samples, and comprehensive documentation.

  • Flexible APIs

    Kinesis Data Analytics provides versatile APIs in Java, Scala, Python, and SQL that are specifically designed for various use cases, including stateful event processing, streaming ETL, and real-time analytics. By leveraging pre-built operators and analytics capabilities, you can expedite the development of Apache Flink streaming applications significantly. Instead of spending months on development, you can now construct these applications in a matter of hours, saving valuable time and effort. The extensibility of Kinesis Data Analytics libraries allows you to perform real-time processing for a wide range of use cases, ensuring flexibility and adaptability.

  • Stateful Processing

    The running application storage of the service securely stores previous and ongoing computations, or state, allowing for comparison of real-time and historical results across any desired time period. It also enables quick recovery in the event of application disruptions. The state is consistently encrypted and incrementally saved within the running application storage.

  • Durable Application Backups

    By making a straightforward API call, you can effortlessly create and delete durable backups of your applications. In the event of a disruption, you can promptly restore your applications from the most recent backup, or choose to restore them to a previous version as needed.

  • Support for Standard SQL

    Service supports standard ANSI SQL.

  • Advanced Stream Processing Functions

    Kinesis Data Analytics provides optimized functions specifically designed for stream processing, enabling seamless execution of advanced analytics tasks like anomaly detection and top-K analysis on your streaming data.

Service integrates with:

Usage use cases

  • Deliver streaming data in seconds.

    Simplify development of data transform and delivery applications. Adpp can deliver data to Amazon S3, Amazon OpenSearch Service, and more.

  • Real-time analytics.

    Effortlessly perform real-time interactive querying and analysis of data, continuously generating timely insights for time-sensitive use cases.

  • Perform stateful processing.

    Leverage long-running, stateful computations to initiate real-time actions, such as anomaly detection, by leveraging historical data trends.

FAQ for Amazon Kinesis Data Analytics

  • What is the main purpose of Amazon Kinesis Data Analytics?

    Main purpose of the Service is to simplify the transformation and real-time analysis of streaming data by leveraging the power of Apache Flink.

  • Does Amazon Kinesis Data Analytics support query data via standard SQL?

    Yes it does. Kinesis Data Analytics supports standard ANSI SQL.

  • How is it possible to get access to server instances used by Amazon Kinesis Video Streams?

    Service is fully serverless and removes complexity of server management from clients. Video streams automatically scales in and out based on created load