To really understand Apache Kafka—and get the most out of this open source distributed event streaming platform—it’s crucial to gain a thorough understanding of Kafka consumer groups. Often paired with the powerful, highly scalable, highly-available Apache Cassandra database, Kafka offers users the capability to stream data in real time, at scale. At a high level, producers publish data to topics, and consumers are used to retrieve those messages.
Kafka consumers are generally configured within a consumer group that includes multiple consumers, enabling Kafka to process messages in parallel. However, a single consumer can read all messages from a topic on its own, or multiple consumer groups can read from a single Kafka topic—it just depends on your use case.