Kafka is a pub-sub tool generally used for message processing, scaling, and efficient handling of large amounts of data.
On the other note, Java Message Service, also known as JMS, is a messaging service created for handling data of more complex systems based on enterprise integration patterns.
Both Kafka and JMS queue are considered as successful solutions and have helped different organizations to communicate effectively through internal teams and servers.
Our primary focus in this article is on Kafka vs java messaging service and how these tools differ from each other in detail.
One of the main differences between Kafka and java messaging services is their programming style. JMS runs on imperative programming style, while Kafka has a reactive programming style.
In the case of Kafka, its system arranges messages in the same order as they were sent from the partition level. But, in the case of JMS, such a provision does not exist, so you need to split the messages as needed.
The second factor that proves the main differences between Kafka and java messaging service is the type of messages. JMS queue works on push type where the enterprise can send messages to their customers.
On the other hand, Kafka is a pull type message system in which customers can pull messages from the broker.
Kafka enables a simple and easy routing system, while JMS offers quite a complex routing system due to the system integration design.
Messages are stored in Kafka for a specific period regardless of whether customers receive them. In Kafka vs JMS queue, JMS offers a disk or in-memory-based storage facility. And once the message is read, it is permanently deleted.
Apache Kafka does not allow you to queue, if you are considering Kafka vs JMS queue. The Pub-sub model is the only way to send messages. But with a JMS-based system, you can queue messages through its routing system.
Apache Kafka allows you to categorize functionality as independently split lugs. This ensures high throughput for Kafka. But, while in the case of JMS-based tools, the splitting is not done sequentially. In the case of JMS-based tools, it leads to throughput output.
Apache Kafka implements a mechanism that allows brokers to decide which message to read first in JMS. JMS uses the first-out approach due to its functionality. The ability and readability options are the important advantage of Apache Kafka, giving it an edge over JMS.
From the above differences between Kafka and java messaging service, it is clear that Apache Kafka is more scalable than JMS. Also, Apache Kafka’s availability is high due to its ability to auto-replicate messages without compromising on simplicity.
Both Kafka and JMS are prominent message management solutions. However, it is always better to use more advanced platforms and architectures like Kafka.
Before deciding Kafka vs JMS queue and which product to use, it is important to consider the suitability of each use case.
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