JMS supports two kinds of Messaging models (Programming models) to support Asynchronous Messaging between
Heterogeneous Systems.
Point to Point Messaging Model and Publish Subscribe Messaging Model are the two different messaging paradigms
supported by Java Message Service (JMS). These messaging paradigms are programming models that support
asynchronous way of messaging between diverse systems.
Point-To-Point Model(P2P Model)
Publish-Subscribe Model(Pub/Sub Model)
Pub/Sub Messaging model is again divided into two categories as shown below:
Durable Messaging Model
Durable Model is also known as Persistent Messaging Model. In this model, Messages are stored in some kind
of store in JMS Server until they deliver to destination properly.
Non-Durable Messaging Model
Non-Durable Model is also known as Non-Persistent Messaging Model. In this model, Messages are not stored
in JMS Server.
Point-To-Point Model Publish-Subscribe Model
1. This model uses Queue as the channel. The 1. Pub-Sub model uses topic as the channel.
Producer sends message to the queue. Consumer pulls Publisher sends message to the topic.
message from the Queue. Consumer subscribe to a topic and gets all
the messages.
2. In this model Message is received by one consumer. 2. In this model message can be received by
We can configure any number of JMS Senders and JMS multiple consumers.
Receivers to a particular queue. However, any message 3. Publishers and subscribers have a timing
Should be delivered to one and only one Receiver. dependency. A client that subscribes to a
3. There is no timing dependency between JMS Sender topic can consume only messages
And JMS receiver. That means the JMS Receiver can published after the client has created a
consume the messages whether it is alive or not when subscription, and the subscriber must
JMS Sender sent that message. continue to be active in order for it to
4. In this model, Destination stores messages till it is consume messages.
consumed by Receiver.
KAFKA
Kafka is a distributed messaging system providing fast, highly scalable and redundant messaging through a pub-sub
model. Kafka, as a distributed system, runs in a cluster.
It is designed as a distributed system which is very easy to scale out.
It offers high throughput for both publishing and subscribing.
It supports multi-subscribers and automatically balances the consumers during failure.
It persist messages on disk
All Kafka messages are organized into topics. If you wish to send a message you send it to a specific topic and if you
wish to read a message you read it from a specific topic. A consumer pulls messages off of a Kafka topic
while producers push messages into a Kafka topic. Lastly, Kafka, as a distributed system, runs in a cluster. Each node
in the cluster is called a Kafka broker.
