So far the following ideas have been introduced: topic, message, partition, producer, consumer and broker. By now, you should understand how Kafka stores messages on disk using commit log, topics and partitions. You should also know how a message is structured.
It’s time to introduce consumer groups, which are the missing piece of message distribution in Kafka.
Traditional messaging patterns: message queue and publish – subscribe, have some limitations as a result of their design.
In the previous post – Apache Kafka Ideas – Part 1, a couple of messaging use cases were introduced. In order to define those cases with Kafka, it is important to understand its ideas. At the very heart of Kafka are topics and partitions. This post explains basic concepts behind them.
Apache Kafka can be thought of as a message broker. It has the following characteristics:
What ideas are behind Kafka and how does it differ from a classical broker? In this series of posts you’ll find out how does Apache Kafka work and be able to run and use Kafka cluster.
Tech Arch Notes 