Kafka V/s RabbitMQ Queuing Systems

Queuing systems are asynchronous in aspect which are built to transfer the data from producer to consumer (mainly known as PUB-SUB model). This complete architecture is recognized as Message Oriented Middleware (Mother). This structures involves the info structure "queue" so the data can be stored to be processed later. It participates in the development of "Service Oriented Structures" and if implemented accurately, these queuing systems can raise the user connection with a website by reducing the load times.

These queuing systems arrived to circumstance because
  • Asynchronous in mother nature. It can help in queuing the info, the buyer can take in it later.
  • Decoupling behaviour of developer and consumer. The manufacturer implementation will not depends on consumers ones and they can run independently.
  • Resilience nature in which if developer or consumer fails, the whole system need not to be halted.
  • These provides buffering which assists with maintaining and optimizing the acceleration of the info which travels on the list of applications.
  • These are scalable in aspect where several applications can send their careers in the queue.

Widely used queuing systems are Apache Kafka and RabbitMQ. So, here are comparisons between the systems.

S. No.

Apache Kafka


Kafka is actually producer-centric, a client server system that is made for the purpose of consumption of high data streams at the publisher end and give the info to a batch of readers (whether online or offline) can be filled together to take the data.

RabbitMQ isserver only system which is built on the protocol AMQP. It is employed for guaranteed delivery of text messages between publisher and customer.


Kafka is mainly designed to to take care of both slow-moving batch consumers and online consumers. It has a capacity to manage almost 100k + events per second. It quite simply serves as "shock absorber" between great happenings exchange between publishers and customers.

If the volume of the info is large and the consumers are too gradual, RabbitMQ will are unsuccessful. It can take care of for the most part 20k+ situations per second. Post 2. 0 version of RabbitMQ, the feature of handling sluggish batch consumers launched.


Kafka persists all the communications by writing them on disk immediately. So that it behaves just like a database safe-keeping system. Hence terabytes of subject matter can be pertained without impacting any performance.

RabbitMQ is designed to assured delivering of announcements to the consumers or buffers it for later use.


It can be an open way to obtain Apache Licence 2. 0 which is written in Scala (JVM).

It is also an available way to obtain Mozilla Community Licence which is written in Erlang.


The broker agents and consumers use Zookeeper to reliably maintain their delivery condition across a cluster, since it doesn't have the feature of note acknowledgements, it considers that the individuals are tracked based on what they used up to now.

Does have the feature of subject matter acknowledgements. The RabbitMQ broker uses Erlang Mnesia to keep up their delivery point out across the clusters.


Kafka has a very simple routing methodology. it uses subject exchanges only.

RabbitMQ offers a rich routing capabilities because it internally uses AMQP 0. 9. 1's exchange, binding and queuing model.


The text messages which should be consumed are sent out in partitions to a subject which operates as "log stream". This stream is carried frontward via consumers.

Messages are released through exchange items to queues. Online consumers get the messages via communication agents. The delivery is to done again in case there is failure, hence it provides guaranteed delivery of text messages for the queues having consumer count 1.


Kafka provides communication buying inside the partitions. So if stringent ordering of announcements are required at consumer end, the consumers have to put in smart fashion.

RabbitMQ provides unordered delivery of emails at consumer end, because relating to AMQP 0. 9. 1 model, to be able to achieve in order delivery there must be "one producer channel, one exchange, one queue and one consumer channel".


The drawback of the system is which it can have a single consumer for every single partition. So, a sluggish message can prevent all other incoming messages, hence different ways of be applied that point to remove the issue. Among the strategy can be to make another consumer group and synchronize with the present consumer. The synchronization is required to all the duplication of emails processing.

In this case, if a slow message is to be consumed by consumers, we can connect increasingly more consumers to the queue to intake the queued announcements that are behind the slow-moving message.


Kafka is mainly suitable for "fast" and reliable consumers.

RabbitMQ is mainly suitable for "slow" and unreliable consumers.

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