简短的回答是“消息确认”。RabbitMQ可以配置为需要消息确认。如果接收方失败，消息将返回队列，另一个接收方可以再次尝试。虽然你可以用自己的代码在Kafka中完成这个任务，但它可以在RabbitMQ中开箱即用。

根据我的经验，如果你有一个需要查询信息流的应用程序，Kafka和KSql是你最好的选择。如果你想要一个排队系统，你最好使用RabbitMQ。

我能想到的唯一好处是事务性功能，其余的都可以用Kafka来完成

Scaling both is hard in a distributed fault tolerant way but I'd make a case that it's much harder at massive scale with RabbitMQ. It's not trivial to understand Shovel, Federation, Mirrored Msg Queues, ACK, Mem issues, Fault tollerance etc. Not to say you won't also have specific issues with Zookeeper etc on Kafka but there are less moving parts to manage. That said, you get a Polyglot exchange with RMQ which you don't with Kafka. If you want streaming, use Kafka. If you want simple IoT or similar high volume packet delivery, use Kafka. It's about smart consumers. If you want msg flexibility and higher reliability with higher costs and possibly some complexity, use RMQ.

Apache Kafka is a popular choice for powering data pipelines. Apache kafka added kafka stream to support popular etl use cases. KSQL makes it simple to transform data within the pipeline, readying messages to cleanly land in another system. KSQL is the streaming SQL engine for Apache Kafka. It provides an easy-to-use yet powerful interactive SQL interface for stream processing on Kafka, without the need to write code in a programming language such as Java or Python. KSQL is scalable, elastic, fault-tolerant, and real-time. It supports a wide range of streaming operations, including data filtering, transformations, aggregations, joins, windowing, and sessionization.

https://docs.confluent.io/current/ksql/docs/index.html

对于etl系统来说，Rabbitmq并不是一个受欢迎的选择，它更适合那些需要简单的消息传递系统和更低吞吐量的系统。

如果你有复杂的路由需求，想要一个内置的GUI来监控代理，那么RabbitMQ可能是最适合你的应用程序。否则，如果你正在寻找一个消息代理来处理高吞吐量并提供对流历史的访问，Kafka可能是更好的选择。

简短的回答是“消息确认”。RabbitMQ可以配置为需要消息确认。如果接收方失败，消息将返回队列，另一个接收方可以再次尝试。虽然你可以用自己的代码在Kafka中完成这个任务，但它可以在RabbitMQ中开箱即用。

根据我的经验，如果你有一个需要查询信息流的应用程序，Kafka和KSql是你最好的选择。如果你想要一个排队系统，你最好使用RabbitMQ。