Apache Kafka vs Spark: Real-time data streaming showdown

Apache Kafka and Apache Spark are open-source tools for big data processing, each with unique features and strengths. Kafka is a distributed streaming platform designed to handle real-time data feeds, while Spark is an open-source distributed computing system for big data processing and analytics. Both technologies serve distinct roles in the big data domain but can be used together to leverage their strengths: Kafka for efficiently collecting and storing streaming data, and Spark for processing and providing analytics based on that data. Companies should consider factors such as use cases, performance indicators, community support, deployment options, and pricing when choosing between these technologies.