Apache Kafka is composed of several key components that work together to provide a powerful distributed streaming platform. The main components of Kafka are:
1. Topics: Topics are the basic units of data in Kafka. They represent streams of messages or events that are categorized and stored in Kafka. Topics are partitioned and replicated across multiple Kafka brokers.
2. Producers: Producers are applications or processes that generate data or messages and publish them to Kafka topics. Producers publish messages to specific topics and can choose to publish them to one or more partitions within a topic.
3. Consumers: Consumers are applications or processes that consume or read data from Kafka topics. Consumers subscribe to specific topics and can consume messages from one or more partitions within a topic.
4. Brokers: Brokers are the servers that make up the Kafka cluster. They are responsible for storing and replicating the data and messages that are produced and consumed by Kafka producers and consumers. Brokers communicate with each other to ensure that data is consistently replicated across the cluster.
5. ZooKeeper: ZooKeeper is a distributed coordination service that is used by Kafka to manage and maintain the state of the Kafka cluster. Kafka uses ZooKeeper to store configuration data, track broker and partition availability, and handle leader election.
6. Connectors: Connectors are pluggable components that enable Kafka to integrate with external systems and data sources. Connectors can be used to ingest data from external sources into Kafka, or to export data from Kafka to other systems such as databases, search engines, or other messaging systems.
Overall, these components work together to provide a highly scalable and fault-tolerant distributed streaming platform that can handle large volumes of real-time data.