Spark vs Hadoop MapReduce

Spark uses a relational database backend for storage Spark processes data in-memory across stages, avoiding the disk I/O overhead of Hadoop MapReduce's intermediate writes Spark can only run on a single machine, making it simpler Spark does not support fault tolerance, which makes it faster