What is the difference between Apache Spark and Kafka?

Apache Spark is designed for processing large data sets - both in batches and streams - by analysing and transforming them. Kafka is for real-time event streaming, meaning it collects, stores, and delivers data as it occurs. So, Spark handles the intensive data processing, while Kafka manages the flow of live data. They are often used together: Kafka supplies live data, and Spark processes it.