We use Kafka as a queue because we understand it very well, but it has a lot of limitations compared to "purpose-built" queuing services.
In that case, sure, theoretically with JMS you can spawn as many parallel consumers as you want and with kafka you're limited to the number of partitions you've configured your topic with, as you can only have one partition per consumer.
But you get so much more out of kafka with consumer groups and partitions when you do complex message processing that would be a lot harder with traditional queues (if you partition based on the same key).
Yes. Then depending on the data it can be difficult-to-impossible to scale past that. Scaling down, of course you can always start fewer consumers, but unless you have many more partitions than consumers or partitions as a multiple of consumers, the load will be unbalanced.
> But you get so much more out of kafka with consumer groups and partitions when you do complex message processing
Well, what's "complex message processing"? If you mean the stream topology is complex or the operations benefit from key sharding I agree. If you mean that some atomic operation is complex, no, it's irrelevant or even bad e.g. the complexity means you need a DLQ/OOO retries, or load per item is so unpredictable you want to work-steal.
