What is Kafka?
Kafka is a relatively new open-source distributed platform for event streaming as it was released in 2011, clearing the way for raw throughput. It is written in Scala and Java and is a pub/sub message bus used in high-ingress data replay and streams. It does not rely on the message queue but instead focuses on appending messages to the log. These messages are left in the log and remain until the consumer opens it or meets the retention limit.
The pull-based approach used by Kafka lets users ask for message batches from particular offsets. This message batching system is used for higher throughput and seamless delivery of messages.
Kafka is used mainly for streaming from A to B, where complex routing is not used. It produces the maximum throughput and is ideal for stream processing, event sourcing, and executing modelling changes to a system as a sequence of events. Kafka is also suitable for processing data in multi-stage pipelines. It is used as a framework for reading, re-reading, storing and analysing streaming data.
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What is RabbitMQ?
RabbitMQ is another message broker that is open-source and used for seamless delivery of messages in complicated routing scenarios. It typically works as a cluster of nodes where queues are dispersed throughout the nodes for replicating high availability and fault tolerance.
RabbitMQ is used by developers to process high-throughput and relevant background jobs and is also used in intercommunication and between applications. RabbitMQ is also used to perform complex routing to people and to integrate numerous services and applications with routing logic that is not trivial.
Web-servers use RabbitMQ for rapid request-response and share loads amongst workers under high load. It is also used for tackling long-running tasks or background jobs like converting PDF, scanning files, or scaling an image.
RabbitMQ vs Kafka
Although Rabbit MQ and Kafka aren’t the same, it all boils down to these two when it comes to choosing messaging options. However, it can be challenging to determine which of the two is better. Therefore, instead of focusing on the cons, make your decision based on your needs, the features of both these services, and the skill sets needed to run these services. These messaging frameworks have variegated capabilities and approach the field of messaging differently.
Here is a chart breaking down the most significant differences between the two:-
|Kafka vs RabbitMQ||RabbitMQ||Kafka|
|Performance||4K-10K messages every second||1 million messages every second|
|Message Retention||Based on Acknowledgment||Based on Policy|
|Type Of Data||Transactional||Operational|
|Consumer Mode||Smart broker/dumb customer||Dumb broker/smart customer|
|Topology||Exchange type: Direct, Fan out, Topic or Header-based||Publish or subscribe based|
|Payload Size||No constraints||Default 1MB limit|
|Usage Cases||Simple use cases||Massive data and high throughput cases|
|Data Flow||Distinct and bounded data flow||Unbounded data flow, with the key-value pairs|
|Messaging||Sends messages to users||It is a log and makes use of continuous messages|
Requirements and Use Cases
It is clear that the choice between both RabbitMQ and Kafka depends on the use case. RabbitMQ’s message broker design is great for use cases with per-message guarantees and certain routing needs. In contrast, Kafka has an append-only log that permits developers to access the stream history and a more direct approach to stream processing.
While RabbitMQ offers developers the traditional queue model, it has also introduced new data structure modelling, an append-only log that has consuming semantics that is non-destructive. This new data structure is made to work in a similar manner to that of Kafka’s persistent log. It is undoubtedly an exciting addition for users of RabbitMQ who also wish to take their streaming use case further. This feature will not only be made to be compatible with the AMQP protocol but will also introduce a stream protocol that is binary-based.
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The developer experience of both Kafka and RabbitMQ has remained chiefly the same. The only thing that has changed is the list of libraries, and most importantly, clients continue to grow. It is all thanks to the work of their particular communities respective of their platforms.
Both client library lists of RabbitMQ and Kafka have steadily grown over the years. More frameworks and languages have garnered fame and rise in popularity. There has been an exponential growth of Kafka Streams as well, and the implementation of a client library makes it much easier to process streaming data amongst developers. It is most commonly used to read data from Kafka, process it, and write it to a different Kafka queue. Therefore, it is a great option for developers looking to develop streaming applications while leveraging relational databases.
This can also be accomplished with RabbitMQ, just like Kafka taking the help of some other pieces, like Spring Cloud Data Flow. With the newly developing streaming changes for RabbitMQ, new ways and newer avenues have been regarding interacting with RabbitMQ on behalf of the developer.
Security and Operations
RabbitMQ has a much more functional and practical administration interface that helps manage users and queues with ease. Kafka, on the other hand, is dependent on JAAS and TLS.
Therefore, the ultimate choice between RabbitMQ or Kafka is entirely dependent on the particular requirements and the specific use case. However, most security scenarios can have a true conclusion with either of the two technologies.
Over the last few years, Kubernetes has affected the operations of services, and a great deal of work has been done to let infrastructure operators run both Kafka and RabbitMQ on Kubernetes. The Kafka Helm chart and RabbitMQ operator are commendable for configuring these services and running them on Kubernetes.
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The choice between RabbitMQ or Kafka can be pretty tricky because of their similar use as well as their rapid improvement with time. The decision should be wholly based on the individual scenario and the use case. If you can, try to get acquainted with both Kafka and RabbitMQ, as it will increase your chances of landing high-paying jobs. Plus, it will make you a more attractive candidate when you sit for job interviews.
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When should you use Kafka vs RabbitMQ?
For developers, Kafka grants access to stream history and direct stream processing, whereas RabbitMQ’s message broker system specialises in use cases that have particular routing requirements and per-message guarantees. However, a new data structure model is under development by RabbitMQl to the append-only log that will focus on bridging the gap in streaming use cases.
Should you use Kafka or RabbitMQ for microservices?
Kafka makes use of high performance, and more straightforward routing approach that is perfect for big data use cases. In contrast, RabbitMQ is used for blocking tasks and has comparatively faster server response time. Both options are great for particular use cases.
Is Kafka higher performance than RabbitMQ?
Both Kafka and RabbitMQ are optimised for performance, which can be challenging to quantify depending on particular use cases. Kafka has very high throughput, whereas RabbitMQ is great for low latency message delivery. It all boils down to the specific use case.