Producer and consumer libraries for Kafka are available in various programming languages and technologies. This allows for multiple different patterns for consumption (for example, fan-out or consumer-groups). In contrast to classic queuing systems, the consumers do not remove the message from the topic but store the individual reading position on the topic.

Various consumers can subscribe to a Kafka topic and consume messages. The received messages are stored in topics, which are the primary storage abstraction. The Kafka cluster itself is a highly available broker that receives messages from various producers. Kafka is based on a simple but powerful pattern. This is an open-source distributed event streaming platform used by many customers for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. One of the most popular technologies in this spaece is Apache Kafka. The range of use cases includes web tracking and other logs, industrial IoT, in-game player activity, and the ingestion of data for modern analytics architecture. Streaming data and event-driven architectures are becoming more popular for many modern systems. This post is written by Philipp Klose, Global Solution Architect, and Daniel Wessendorf, Global Solution Architect. Post Syndicated from James Beswick original

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