We think of a streaming platform as having three key capabilities:

• It lets you publish and subscribe to streams of records. In this respect it is similar to a message queue or enterprise messaging system.
• It lets you store streams of records in a fault-tolerant way.
• It lets you process streams of records as they occur.
  

What is Kafka good for?

It gets used for two broad classes of application:

• Building real-time streaming data pipelines that reliably get data between systems or applications
• Building real-time streaming applications that transform or react to the streams of data
  

To understand how Kafka does these things, let's dive in and explore Kafka's capabilities from the bottom up.

First a few concepts:

• Kafka is run as a cluster on one or more servers.
• The Kafka cluster stores streams of records in categories called topics.
• Each record consists of a key, a value, and a timestamp.
  

Kafka has four core APIs:

• The Producer API allows an application to publish a stream of records to one or more Kafka topics.
• The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them.
• The Streams API allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams.
• The Connector API allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to a table