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This video explains the basic concepts of Apache Kafka - an event store and stream-processing platform.

Apache Kafka is an open-source distributed event store and stream-processing platform. Kafka was originally developed at LinkedIn, and was subsequently open sourced in early 2011. The software received its name after a German-speaking writer Franz Kafka because it is "a system optimized for writing".
From a developer's point of view Kafka works very similar to message queuing services: producers write messages to topics and consumers read and process messages.
What makes Kafka different is that it provides high-throughput and low-latency while preserving the order of messages. This makes the platform a very good choice for systems that handle real-time data at scale.
Kafka also allows storing messages in topics for as long as it is necessary. The platform does not have a limit on how long a message can be stored in a topic. The size of the topic is limited only by disk space available on a cluster.
Kafka works on bare-metal hardware, virtual machines, and containers. It can run on-premises as well as in the cloud. Today, a variety of cloud vendors offer fully managed Kafka environments.
Today, Kafka is used by thousands of big and small companies. Netflix uses Kafka for data analytics, Uber for passing data from mobile applications to backend services, Etsy for communication between backend services, LinkedIn for data ingestion, Spotify for merchant analytics.
As you can see, Kafka is a battle-tested platform for building real-time stream-processing systems that can handle data at large scale.

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