Home  >  Blog  >   Apache Kafka

Kafka vs RabbitMQ

Rating: 4.8

A software architect who deals with various microservice-based systems often faces the question, “Should I use Kafka or RabbitMQ?”. Due to some reasons, many developers consider these technologies as exchangeable. Although this is right for some cases, there are some principal differences between these platforms. In this Kafka vs RabbitMQ article, we will look at those principle differences.

So, let’s begin with understanding what exactly is Kafka and RabbitMQ.

Table of Contents - Kafka vs RabbitMQ

What is Kafka?

Kafka is a freeware distributed sub/pub message system. It was released in 2011, and it acts as middleware storage between two applications. Producer stores and writes messages in the Kafka cluster. On the other side, the Consumer consumes the messages from the cluster.

Do you want to master Apache Kafka? Then enroll in "Apache Kafka Online Training" This course will help you to master Apache Kafka

What is RabbitMQ?

RabbitMQ is the most commonly used, freeware, and multi-purpose message broker. It was released in 2007; it is the main element in messaging systems. At present, we use it to stream applications. RabbitMQ can handle background tasks or acts as a message broker between the microservices. It helps web applications in minimizing the loads. It reduces the delivery period of servers for those resources that were time-taking.

MindMajix Youtube Channel

Kafka vs RabbitMQ - Major Differences

Following are the key differences between Kafka and RabbitMQ.

#1. Architecture

Kafka Architecture 

Kafka’s architecture uses a large amount of publish-subscribe messages and a flow platform that is fast and durable. The tough message store, such as logs, uses server clusters that store various records in topics. Every Kafka message features a value, timestamp, and key. The dumb broker or smart consumer model does not track the consumer messages and returns unread messages.

Related Article: Apache Kafka Interview Questions and Answers

RabbitMQ Architecture 

RabbitMQ Architecture uses an all-around message broker that involves changes in request/reply, pub/sub, and point-to-point communication designs. The utilization of a smart broker and dumb consumer method enables trustworthy message delivery to the consumers with the same speed as a broker controlling the consumer's state.

Through asynchronous or synchronous communication, RabbitMQ provides enough support for different plugins comprising Node.js, .Net Client Libraries, and Java.

#2. Sources


We develop Kafka in Scala. In LinkedIn, we use it to connect distinct internal systems. After that, Apache adopted Kafka in the environment of the products.


It is initially developed for implementing AMQP, an open wire protocol to message with robust routing features. Although java has a messaging system like JMS, for non-java applications, it is not useful because they require distributed messaging that is heavily restricted to any inclusion case, either monolithic or microservice. Therefore, cross-browser resilience becomes valid for the freeware message brokers with the emergence of AMQP.

#3. Push/Pull Model


Kafka uses the Pull model where consumers make message requests in groups from a particular offset. It also enables long-pooling that interrupts tight loops when no message crosses the offset. The pull model stays logical for Kafka because of its partitions. The pull platform provides message order in a block without conflicting consumers.


RabbitMQ pushes the messages to the consumers that comprise a prefetched restricted configuration that is important to stop the consumer from becoming affected by the multiple messages. We can use the configuration for low latency messaging. 

The method’s objective is to rapidly distribute the messages separately, besides an assurance that all of them are parallelized equally, and consumers process the messages in an ordered queue.

#4. Message Routing


Kafka does not permit consumers to filter the messages in the topic before querying them. A subscribed consumer gets all the messages in a division without error. A developer can use a Kafka stream job for reading and filtering messages. Kafka’s stream job pushes the messages to another topic, and consumers can subscribe to that topic.


RabbitMQ routes the messages to the subscribers of the message exchange according to the subscriber-based routing rules. Topic Exchange routes the messages according to the header named “routing_key.” 

On the other hand, headers exchange routes according to the message headers. Both topic exchange and header messages permit consumers to define the kind of messages they want to receive.

#5. Message Retaining


Kafka retains all the messages by design till a configured timeout per topic. Kafka is not concerned with its consumers’ consumption condition in terms of message retention since it serves as a message log.


RabbitMQ ejects the messages from the storage as early as consumers consume them. We cannot change this behavior, and this is a part of message brokers.  

Apache Kafka vs RabbitMQ - Some Other Differences are:

Basis for ComparisonKafkaRabbitMQ
Kafka is freeware through Apache License 2.0.
RabbitMQ is freeware through the Mozilla Public License.

Developer Experience

Kafka has advanced features for developers; although it only moves a java client, there is an increasing list of communal freeware clients, natural projects, and an adapter SDK that enables us to develop our system integration. Here “.properties” files perform a lot of the configuration. 
The client libraries of RabbitMQ are appropriately documented and mature and support Spring, Java, PHP, .NET, Ruby, Python, Javascript, Go, Objective-C, Swift, and Elixir- with various other development and client tools through community plugins.

Client Libraries

Kafka has various libraries like Python, Ruby, Java, and Node.js.
RabbitMQ has various libraries like Python, Clojure, Python, Node.js, Java, and Go.

High Availability

It supports High Availability.
RabbitMQ supports High Availability.

Developed in

Kafka is developed in Scala.
RabbitMQ is developed in Erlang.

Associated Queues

It does not support associated queues.
RabbitMQ supports associated queues. This feature provides a method of load balancing of a single queue throughout clusters or nodes. 

Hosting and Enterprise Support

Kafka is accessible from CloudKarafka. CloudKarafka provides a free hosted Kafka as a service. 
RabbitMQ is accessible from CloudAMQP. The CloudAMQP operates and provides support to the biggest fleet of the RabbitMQ Cluster.

Difficult Routing Cases

It can perform difficult routing cases.
RabbitMQ cannot perform difficult routing cases


Kafka endorses those transactions that demonstrate the “read-process-write” model accomplished from/to the  Kafka topics.
RabbitMQ does not assure atomicity even though the transaction carries only one queue. 

Secure Authentication

Kafka supports OAuth2, Standard Authentication, and Kerberos.
RabbitMQ supports OAuth2 and Standard Authentication.


Although Kafka and RabbitMQ are sometimes exchangeable, their implementations are distinct from each other. Therefore, we cannot consider them as the same kinds of tools; Kafka is a distributed streaming platform, and RabbitMQ is a message broker. Developers and Solution architects must recognize these differences and strongly consider which of these tools they must use in the given scenario. I hope this article provides the required information about the differences between Kafka and RabbitMQ,

If you have any queries in this Kafka vs RabbitMQ blog, let us by commenting in the below section.

Join our newsletter

Stay updated with our newsletter, packed with Tutorials, Interview Questions, How-to's, Tips & Tricks, Latest Trends & Updates, and more ➤ Straight to your inbox!

Course Schedule
Apache Kafka TrainingApr 23 to May 08View Details
Apache Kafka TrainingApr 27 to May 12View Details
Apache Kafka TrainingApr 30 to May 15View Details
Apache Kafka TrainingMay 04 to May 19View Details
Last updated: 03 Apr 2023
About Author

Viswanath is a passionate content writer of Mindmajix. He has expertise in Trending Domains like Data Science, Artificial Intelligence, Machine Learning, Blockchain, etc. His articles help the learners to get insights about the Domain. You can reach him on Linkedin

read more
Recommended Courses

1 / 15