Head First Kafka

Introduction

Apache Kafka is an open-source, distributed event streaming platform that is widely used for building real-time data pipelines and streaming applications. It allows for the storage and processing of large amounts of data in a fault-tolerant and scalable way.

Kafka is a publish-subscribe system, which means that it allows for the separation of data producers and data consumers. Producers write data to topics, and consumers read from those topics. This decoupling of producers and consumers allows for a high degree of flexibility and scalability.

One of the key features of Kafka is its ability to handle large amounts of data in real-time. It achieves this by using a distributed architecture, where data is replicated across multiple nodes for fault tolerance and scalability. This also allows for the ability to handle high throughput and low latency.

Another important feature of Kafka is its ability to handle data streams in a fault-tolerant way. If a node in a Kafka cluster goes down, the data is still available and can be replayed to other nodes. This makes it well-suited for mission-critical applications that require high availability.

Kafka also provides a variety of built-in tools for data management and processing, such as Kafka Connect and Kafka Streams. These tools allow for easy integration with other systems and easy processing of data streams.

Kafka is used by many companies and organizations for a variety of use cases, such as real-time analytics, data integration, and event-driven applications. Some examples of companies that use Kafka include LinkedIn, Netflix, and Uber.

Overall, Kafka is a powerful and flexible platform for building real-time data pipelines and streaming applications. Its ability to handle large amounts of data in real-time, its fault-tolerance, and its built-in data management and processing tools make it a valuable tool for many different use cases.

Reference

• https://kafka.apache.org/