Compare ActiveMQ vs. Apache Kafka in 2026

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Description

Apache ActiveMQ® stands out as the leading open-source, multi-protocol message broker built on Java. It accommodates widely accepted protocols, allowing users to take advantage of diverse client options across various programming languages and platforms. Clients can connect using languages such as JavaScript, C, C++, Python, .Net, and more. The integration of multi-platform applications is made seamless with the widely-used AMQP protocol. Furthermore, web applications can communicate effectively through the STOMP protocol over websockets. ActiveMQ also facilitates the management of IoT devices by leveraging MQTT. It not only supports existing JMS infrastructures but also extends beyond them, providing the robustness and adaptability necessary for any messaging scenario. Presently, there are two distinct versions of ActiveMQ: the traditional "classic" broker and the innovative "next generation" broker known as Artemis. As Artemis develops to match the feature set of the Classic code-base, it is set to evolve into the next major release of ActiveMQ. Initial documentation for migration is accessible, along with a development roadmap outlining the future of Artemis, ensuring users have the guidance they need for a smooth transition. This evolution signifies a commitment to continual improvement and adaptation in a rapidly changing technological landscape.

Description

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.