The Clean Difference Between Kafka and Message Queue (RabbitMQ)

Kafka and RabbitMQ Play an essential role in modern distributed Architecture. In a real-life use case, both of them solves the different problem. Before diving into the details of the differences, let us understand some basics start with Kafka.

“Kafka is a distributed event streaming platform”.

What is an event Streaming?

“Event streaming platform(ESP) helps in processing data point in the real-time”.

In Layman terms of explaining it, everything in the business world is an event, For Example, In E-commerce business where events are “order placed, payment made, Order Confirmed, Order shipped”. In Company Like UBER/OLA/LYFT Car Booked, Trip End, Trip Cancelled. We can derive events from any business.

Imagine this billion of the business event data points are accumulated in real-time and helps in making the business decision. For example, In Uber, when the cars are in high demand, they will increase the cost of the trip in the real-time. Tools like Kafka helps to solve these business requirements.

“ RabbitMQ is an open-source message broker.”

What is a message broker?

A message broker is an architectural pattern used for message validation, transformation, and routing. It mediates communication among applications,

In LayMan Term of Explaining it, Imagine you have a Mobile phone which you send one message to your friend and his mobile switched off. As soon as he turned ON the Mobile message will be sent to his mobile, The Networks Service provider will act as a message broker and queue up all the SMS until its get delivered.

Technically Calling it as the asynchronous message process” where the message sender doesn’t have to wait for the message to get delivery, once the SMS goes out of it will be queued and sent to the target character.

Why the Confusion a-raised between Kafka and RabbitMQ?

Some common reasons for these conflicts

1. Both Kafka and RabbitMQ Share the common goal of achieving the Asynchronous processing(doing Operations at the background)
2. Kafka Internally uses the Message Broker Architectural pattern, so some work which was done by the RabbitMQ Can be Achieved here but not in all scenario.

The Differences

1. Real-Time Data Processing

Kafka: Stream API provided by the Kafka Help in achieving real-time data processing.

RabbitMQ: No provision to processing on a queue level

2. Order of data

Kafka: Order is maintained

RabbitMQ: Order might change when only one consumer available for one queue. If more than one consumer, their great chance of consumer failed to process that unit and the other unit get process by the second consumer.

3. Time to Live of the Data

Kafka: Data which send to Kafka are strongly persistent and event after all the consumer received the message it will hold up the data. We can even do the replay of the data.

RabbitMQ: Data lives in the queue until read by the target consumer. In case of the failure, the message broker will flush the data based on the queue configuration.

4. Communication Between the Services

Kafka: Publisher and Subscription model.

RabbitMQ: Queue name and routing rule.

5. Timed Message/Timer

Kafka: No Timer.

RabbitMQ: Supports timed messages delivery to the consumer.

Finally, Some Use Cases example:

Kafka :

1. Real-Time Data Processing
2. Stock trading processing
3. Uber Example for Cost increasing
4. Order updates in e-commerce

RabbitMQ :

1. Sending Email
2. Dual write on the data on DB replication
3. Timed reminder