Apache Kafka is an open-source distributed event streaming platform designed for high-throughput, fault-tolerant data pipelines, real-time streaming analytics, and log aggregation. Kafka was initially developed by LinkedIn and later donated to the Apache Software Foundation. It allows applications to publish and subscribe to data streams, process those streams in real time, and store them reliably.

Kafka operates as a distributed, partitioned, and replicated commit log. Its architecture consists of producers, which publish messages to topics, and consumers, which read those messages. Kafka brokers (servers) manage the distribution and replication of messages, ensuring fault tolerance and scalability. Kafka's high throughput and low latency make it ideal for applications requiring real-time data processing, such as fraud detection, log analysis, and sensor data collection from IoT devices.

Kafka's unique design allows it to handle millions of messages per second across many clients, and it is commonly integrated with stream processing tools like Apache Flink or Apache Spark. With its Kafka Streams API, Kafka can also be used to build complex data-processing pipelines. Kafka is a key component in modern data architectures, facilitating the seamless movement of large volumes of data in real-time.