Apache Spark and Hadoop are both open-source distributed computing frameworks. The main difference between the two is that Apache Spark is a fast and general-purpose engine for large-scale data processing, while Hadoop is a batch-oriented distributed computing system designed for large-scale data storage and processing.
For example, Apache Spark can be used to quickly process large datasets in parallel, while Hadoop is better suited for storing and managing large amounts of data. Apache Spark also supports data streaming and machine learning algorithms, while Hadoop does not.