Google Cloud Pub/Sub, the jewel of streaming data

Kafka looks like and ordered queue, there no deliver backoff, so if a message has a problem, it doesn't advance to the next one. Google Cloud Pub/Sub looks like more a SET of messages, and kafka like a LIST. In kafka a same message will repeat instantaneously while it is being NACKED, on the other hand Google Cloud Pub/Sub will just deliver another and apply a backoff to the previous NACKED one, never stopping on a single message forever. Dead Letter Queues are innate to Google Cloud Pub/Sub while in Kafka is not a feature at all. One can configure the maximum amount of NACKs before sending a message to the DLQ, this is very powerful if combined with exponential backoff. Google Cloud Pub/Sub lets users scale consumers at will with no constraint, Kafka has a rather convoluted concept of partitions and consumer groups that requires one to plan ahead how many consumers they would like to plug to the queue because these constraints prevent a free scaling of consumers. If you plan for N consumers, you have to probably stick to that N forever or recreate your Kafka topic, in Confluent Cloud this is somewhat solved, but looks like a solution to a problem that should even exist in the first place.