Kafka vs Other Messaging Systems

Apache Kafka

Though Apache Kafka was originally designed as a messaging queue, the software quickly grew popular as an event streaming platform and currently handles trillions of events each day. Wherever there is a requirement for message queuing or a message broker system, Kafka is a good option.

Features

1. Much like a messaging system or message queuing system, Apache Kafka allows publishing and subscribing to streams of records.

2. Records streams are stored using a fault-tolerant approach.

3. It is scalable since it allows decoupling of applications.

4. It is easily available.

5. It offers high throughput to manage real-time data transfers.

Why Kafka?

The major advantage of using Kafka lies in its ability to parallelize topics using partitions, with the possibility for each partition to be hosted over different machines. Consumers can access topics in parallel. You can also allow multiple consumers to access multiple partitions, making scaling easier. This unique feature significantly increases Kafka’s throughput for processing message queues.

Kafka’s excellent scaling capabilities allow it to handle large workloads. LinkedIn, for example, uses Kafka to manage 300 billion user events every day.

It’s often a preferred choice over other message queues for real-time data pipelines. Overall, it’s a versatile platform that can support many use cases, including data streaming, message broker systems, log aggregator, etc.

ActiveMQ

Apache ActiveMQ is a popular open source messaging service written in Java. It was originally created in 2004 by LogicBlaze as an open source message broker and later donated to the Apache Software Foundation in 2007.

Like all other message brokers, it serves as a communication platform between multiple applications existing ...