Spring-Kafka vs. Spring-Cloud-Stream (Kafka) - spring

Question

Using Kafka as a messaging system in a microservice architecture what are the benefits of using spring-kafka vs. spring-cloud-stream + spring-cloud-starter-stream-kafka ?
The spring cloud stream framework supports more messaging systems and has therefore a more modular design. But what about the functionality ? Is there a gap between the functionality of spring-kafka and spring-cloud-stream + spring-cloud-starter-stream-kafka ?
Which API is better designed?
Looking forward to read about your opinions

Answer 1

Spring Cloud Stream with kafka binder rely on Spring-kafka. So the former has all functionalities supported by later, but the former will be more heavyweight. Below are some points help you make the choice:
If you might change kafka into another message middleware in the future, then Spring Cloud stream should be your choice since it hides implementation details of kafka.
If you want to integrate other message middle with kafka, then you should go for Spring Cloud stream, since its selling point is to make such integration easy.
If you want to enjoy the simplicity and not accept performance overhead, then choose spring-kafka
If you plan to migrate to public cloud service such as AWS Kensis, Azure EventHub, then use spring cloud stream which is part of spring cloud family.

Answer 2

Use Spring Cloud Stream when you are creating a system where one channel is used for input does some processing and sends it to one output channel. In other words it is more of an RPC system to replace say RESTful API calls.
If you plan to do an event sourcing system, use Spring-Kafka where you can publish and subscribe to the same stream. This is something that Spring Cloud Stream does not allow you do do easily as it disallows the following
public interface EventStream {
String STREAM = "event_stream";
#Output(EventStream.STREAM)
MessageChannel publisher();
#Input(EventStream.STREAM)
SubscribableChannel stream();
}
A few things that Spring Cloud Stream helps you avoid doing are:
setting up the serializers and deserializers