A message broker has very different characteristics and use cases than a data streaming platform like Apache Kafka. A business process requires more than just sending data in real time from a data source to a data sink. Data integration, processing, governance, and security must be reliable and scalable end-to-end across the business process. This blog post explores the capabilities of message brokers, the relation to the JMS standard, trade-offs compared to data streaming with Apache Kafka, and typical integration and migration scenarios. A case study explores the migration from IBM MQ to Apache Kafka. The last section contains a complete slide deck that covers all these aspects in more detail.

Message Broker vs. Apache Kafka -> Apples and Oranges

TL;DR: Message brokers send data from a data source to one or more data sinks in real-time. Data streaming provides the same capability but adds long-term storage, integration, and processing capabilities.

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