Kafka can scale and distribute individual streams across the cluster. That is, the entire "database" is distributed across nodes. With postgres, your unit of sc

Kafka can scale and distribute individual streams across the cluster. That is, the entire "database" is distributed across nodes. With postgres, your unit of scalability is the entire database. You can't natively have some tables on one node and some tables on another node, for example. Kafka is also just more optimized for what it does. Postgres is a superset of what kafka does, so kafka is unsurprisingly better able to optimize for its usecase. It has a zero-copy protocol that can shuttle data to/from disk to/from the network without bringing it into memory (using the sendfile syscall). It doesn't wait for disk writes when doing writes, because it achieves durability via replication. Also, don't forget the things you'd have to do when implementing consumers. How will you load balance streams between consumers? Meaning, if you have a stream and you want multiple consumers to burn it down at a time, how can you make sure they aren't duplicating work and they can handle the consumer group growing/shrinking? How will you handle checkpointing where each consumer tracks what they've done so far? What about streams' data rolling off? All of this is doable with pg, but you'd have to implement it yourself. With kafka and its client drivers, this is handled for you.