What is Apache Kafka?

The Apache Software Foundation has created the open-source framework for processing known as Apache Kafka. It offers a uniform, high-throughput, low-latency platform for managing real-time data feeds and is used for developing real-time data pipelines and streaming applications.  

Kafka is designed to be highly scalable and can handle millions of events per second. As a result, it is mostly used in scenarios where large amounts of data need to be processed and analyzed in real-time, such as in log analysis, event tracking, and real-time analytics.

Kafka works by organizing data into topics divided into one or more partitions. Producers write data on these topics, and consumers read data from them. Kafka’s distributed architecture allows it to handle large amounts of data and provides high availability and fault tolerance.

In addition to its stream processing capabilities, Kafka also includes a message broker, which allows it to be used as a messaging system for distributed systems. As a result, it is the mostly used choice for building real-time data pipelines and streaming applications and is used by many large companies for data processing and analysis.

It is an open-source stream processing software platform built on Java and Scala. It is a contribution from LinkedIn to the Apache Software Foundation. The aim of Apache Kafka is to provide a high throughput, standardised, low-latency architecture for managing real-time data sources. Typically, Kafka used a performance-optimised TCP-based protocol. As a result, it is pretty rapid and can write two million times per second.

Furthermore, it guarantees that no data will be lost.

Apache Kafka is frequently used for real-time analytics, data input into Hadoop and Spark, error recovery, and website activity monitoring.