Kafka vs Mosquitto: What are the differences?
Kafka: Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design; Mosquitto: An open source message broker that implements the MQTT protocol. It is lightweight and is suitable for use on all devices from low power single board computers to full servers.. The MQTT protocol provides a lightweight method of carrying out messaging using a publish/subscribe model. This makes it suitable for Internet of Things messaging such as with low power sensors or mobile devices such as phones, embedded computers or microcontrollers.
Kafka and Mosquitto can be categorized as "Message Queue" tools.
Kafka is an open source tool with 12.7K GitHub stars and 6.81K GitHub forks. Here's a link to Kafka's open source repository on GitHub.
Uber Technologies, Spotify, and Slack are some of the popular companies that use Kafka, whereas Mosquitto is used by Teleolabs, Xanview Ltd, and Future Corporation. Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to Mosquitto, which is listed in 3 company stacks and 3 developer stacks.
What is Kafka?
What is Mosquitto?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Mosquitto?
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with Mosquitto?
Sign up to get full access to all the tool integrationsMake informed product decisions
Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.
Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.