Introduction
Features/Benefits of Kafka
Real-time data streaming
Kafka is designed for real-time data streaming, making it suitable for use cases such as IoT, log aggregation, and most event-driven architectures.
Durability
Data in Kafka is stored on disk and replicated across multiple brokers, providing durability and fault tolerance.
Fault tolerance
Kafka is designed for high availability and provides features for replicating data and automatically failing over to backups in the event of a failure.
Scalability
Kafka is designed for scalability and can handle high volumes and velocity of data, making it suitable for use in large-scale, data-intensive applications.
Processing of data in real-time
Kafka allows real-time processing of data as it is produced, making it possible to perform real-time analytics, transformations, and other processing tasks.
Integration
Kafka provides a wide range of APIs and simple integration options, making it easy to integrate with other systems and technologies, such as Apache Spark, Apache Storm, etc.