JMS Message Broker vs Apache Kafka Data Streaming
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Message Broker and Apache Kafka: Trade-Offs, Integration, Migration

A Message broker has very different characteristics and use cases than a data streaming platform like Apache Kafka. Data integration, processing, governance, and security must be reliable and scalable 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.
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Request Response Data Exchange with Apache Kafka vs CQRS and Event Sourcing
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When to use Request-Response with Apache Kafka?

How can I do request-response communication with Apache Kafka? That’s one of the most common questions I get regularly. This blog post explores when (not) to use this message exchange pattern, the differences between synchronous and asynchronous communication, the pros and cons compared to CQRS and event sourcing, and how to implement request-response within the data streaming infrastructure.
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JMS Message Queue vs Apache Kafka Comparison
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Comparison: JMS Message Queue vs. Apache Kafka

Comparing JMS-based message queue (MQ) infrastructures and Apache Kafka-based data streaming is a widespread topic. Unfortunately, the battle is an apple-to-orange comparison that often includes misinformation and FUD from vendors. This blog post explores the differences, trade-offs, and architectures of JMS message brokers and Kafka deployments. Learn how to choose between JMS brokers like IBM MQ or RabbitMQ and open-source Kafka or serverless cloud services like Confluent Cloud.
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