Kafka is a tool for handling and processing large amounts of streaming data and for doing it in real-time. It was originally developed at LinkedIn by several developers who needed a system that could do that and thus Kafka was created. The main goal of Kafka is to make sure all the data stays correct and intact, from the time it arrives at your company’s servers to when it’s processed.
Why Kafka?
- High speed and throughput: Kafka can handle hundreds of thousands of messages per second, which enables it to deal with a high volume of data
- Scalability: Kafka is designed in such a way that when you need to scale up, it can be easily done by adding more nodes
- Durability: Kafka persists all the messages so they are never lost
- Reliable messaging semantics: Messages are never lost, duplicated, or out of order
- Flexibility: Kafka is designed to handle all types of streaming data and it also allows you to process the data in real-time
- Easy to set up: Kafka is very easy to set up, it doesn’t need that much configuration and is very minimal
- Ease of use: Kafka has a simple and easy-to-understand API which makes it very easy to build your applications
- Use cases: Kafka can be used in many different use cases, for example, real-time analytics, operational data processing, machine learning, and IoT applications, just to name a few
- Cost-effectiveness: Kafka is cost-effective because it requires less hardware than other alternatives
- No single point of failure: Kafka is designed in such a way that it doesn’t have any single points of failure, this makes it very reliable
- Integration With Other Systems: Kafka can easily be integrated with other systems, making it easy to connect any system with Kafka