3 Integrations with IBM Event Automation

View a list of IBM Event Automation integrations and software that integrates with IBM Event Automation below. Compare the best IBM Event Automation integrations as well as features, ratings, user reviews, and pricing of software that integrates with IBM Event Automation. Here are the current IBM Event Automation integrations in 2026:

  • 1
    IBM Cloud
    IBM Cloud® capabilities enable business agility and resiliency. Explore the platform that gives you 2.5x value. Designed for industry, security and the freedom to build and run anywhere. Business workflow transformation with automation and AI. Strong technology partner ecosystem that delivers value for industry needs. Industry and business domain expertise and solutions. Automated and auditable processes. Unique capabilities for the highest levels of cloud security and monitoring. Consistent security and controls posture across all applications. Containerized capabilities for DevOps, automation, data and security. Ease of integration and a consistent application development lifecycle. Advanced technologies including IBM Watson®, analytics, IoT, and edge.
  • 2
    Apache Kafka

    Apache Kafka

    The Apache Software Foundation

    Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.
  • 3
    Apache Flink

    Apache Flink

    Apache Software Foundation

    Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.
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