Apache Kafka and Use Cases
Why Kafka?
With new domains growing every day like IoT, mobile gaming, and data analytics, developers are looking for a solution to consume the data in a rapid and coherent way. This is exactly the place where Apache Kafka fits in.
According to Kafka's official documentation, Apache Kafka is a community-distributed event streaming platform capable of handling trillions of events a day.
Moreover, the popularity of Kafka has increased in recent times due to its robustness. According to data published by RedMonk questions related to Apache-Kafka are increasing rapidly on google, stack overflow, and Github. In the graph below, you can see that GitHub interest has grown exponentially.
What is Apache-Kafka?
Kafka is open-source software originally developed by Linkedin which provides a framework for building real-time data pipelines and real-time streaming applications. It is used to publish and consumer stream of records using the pub-sub model. Kafka allows your services to process the data as soon as it becomes available.
Use in Industry
- Retail and e-commerce - In this era of cut-throat competition among e-commerce giants it has become more important to process the data in real-time. Websites can ensure that they create robust, frictionless, and seamless inventory management, payment system, and tracking system. Currently, Walmart, Shopify, and many more are among the top companies leveraging the power of Apache Kafka.
- Retail Banking -With the emerging trends in the retail industry, service providers need to view all the information of their customers across various channels in real-time. Some of the use cases are personalized promotions and fraud detection.
- HealthCare-By streaming data from various sources, healthcare apps can provide numerous options to their customer and can give them better recommendations.
Capital One: Commander — Decoupled, Immutable REST APIs with Kafka Streams
Cerner: Ingesting complex healthcare data with Apache Kafka at Cerner
Hope this article would be helpful to develop a better understanding of Kafka and also know better about its use cases.
