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Apache Kafka

Do you want to use Kafka? Or do you need a Queue?

Nastel Technologies®
November 14, 2022

Do you want to use Kafka? Or do you need a message broker and queues? While they can seem similar, they have different purposes. I’m going to explain the differences, so you don’t try to brute force patterns and concepts in Kafka that are better used with a message broker.

 

Partitioned Log

Kafka is a log. Specifically, a partitioned log. I’ll discuss the partition part later in this post and how that affects ordered processing and concurrency.

Kafka Log

When a producer publishes new messages, generally events, to a log (a topic with Kafka), it appends them.

Kafka Log

Events aren’t removed from a topic unless defined by the retention period. You could keep all events forever or purge them after a period of time. This is an important aspect to note in comparison to a queue.

With an event-driven architecture, you can have one service publish events and have many different services consuming those events. It’s about decoupling. The publishing service doesn’t know who is consuming, or if anyone is consuming, the events it’s publishing.

Consumers

In this example, we have a topic with three events. Each consumer works independently, processing messages from the topic.

Consumers

Because events are not removed from the topic, a new consumer could start consuming the first event on the topic. Kafka maintains an offset per topic, per consumer group, and partition. I’ll get to consumer groups and partitions shortly. This allows consumers to process new events that are appended to the topic. However, this also allows existing consumers to re-process existing messages by changing the offset.

Just because a consumer processes an event from a topic does not mean that they cannot process it again or that another consumer can’t consume it. The event is not removed from the topic when it’s consumed.

 

Commands & Events

A lot of the trouble I see with using Kafka revolves around applying various patterns or semantics typical with queues or a message broker and trying to force it with Kafka. An example of this is Commands.

There are two kinds of messages. Commands and Events. Some will say Queries are also messages, but I disagree in the context of asynchronous messaging.

Commands are about invoking behavior. There can be many producers of a command. There is a required single consumer of a command. The consumer will be within the logical boundary that owns the definition/schema of the command.

Sending Commands

Events are about notifying other parts of your system that something has occurred. There is only a single publisher of an event. The logical boundary that publishes an event owns the schema/definition. There may be many consumers of an event or none.

Publishing Events

Commands and events have different semantics. They have very different purposes, and how that also pertains to coupling.

Commands vs Events

By this definition, how can you publish a command to a Kafka topic and guarantee that only a single consumer will process it? You can’t.

Queue

This is where a queue and a message broker differ.

When you send a command to a queue, there’s going to be a single consumer that will process that message.

Queue Consumer

When the consumer finishes processing the message, it will acknowledge back to the broker.

Queue Consumer Ack

At this point, the broker will remove the message from the queue.

Queue Consumer Ack Remove Message

The message is gone. The consumer cannot consume it again, nor can any other consumer.

 

This article originally appeared on codeopinion.com. To read the full article, click here.

Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering tools for Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT, IBM Cloud Pak for Integration and many more.

 

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