I think Gepsens argument was that your not achieving the same pattern, rather your achieving a subset of the pattern where several important considerations in dealing with a distributed system have been ignored and/or are unsupported. Once you do add those features back in then you basically arrive at Kafka and all the complexity involved with standing it up, so Redis isn't really an Apples to Apples comparison. While it certainly might work for certain use cases (and indeed appears to do so), many of the use cases that Kafka is necessary for would end up being just as complicated to setup Redis to support.

I think this is largely a rephrasing of one of the findings of dealing with NoSQL vs. Relational DBs, which is that for a subset of problems relational DBs have been used to solve in the past, NoSQLs are perfectly capable of replacing them, but not every problem a relational DB handles can be handled by a NoSQL without investing significant time and effort layering more complex systems on top, at which point you've basically implemented a poorly optimized ad-hoc relational DB. In this case, Redis, with the new stream type is capable of handling a subset of problems that have previously required Kafka to solve, but it isn't itself a replacement for Kafka in all situations since there are several important features of Kafka that aren't available in Redis.