Kafka is a distributed, fault-tolerant and highly scalable message broker.
Redis is a very fast key/value (another other data types) store.
I suppose that at a high level Logstash can be compared to Kafka but IME Logstash can't handle scale. It's trivially easy to bring Logstash to its knees.
Elasticsearch is, well, a search engine.
There are many use cases Redis pub/sub can't serve beyond just scalability.
You can somewhat compare Kafka to Logstash but Kafka has no processing, it's purely a distributed log writing/reading/storage system that also scales far more than logstash can. You write data to it and then read from it with a basic messaging abstraction of topics and partitions.
As multiple comments have stated above, Kafka is really a distributed message subsystem. Its core interface is a set of topics that one can publish to, and that consumers can read from (in other words, a pub-sub system). Kafka doesn't inspect the message payload at all.
Elasticsearch is a unstructured (to some extent) document store that's optimized around document search. So at the very least, the payload is important when using Elasticsearch.
Elasticsearch is all about saving, inspecting, indexing and retrieving your data through a rich document-based model and search-optimized methods.
ES might be able to do the same thing functionally because it operates at a higher level but ultimately will never scale or be as simple in access as Kafka.
