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Apache Spark works faster when the data fits into memory, Spark processes data in memory which makes it faster in processing while MapReduce pushes data to disk after processing it. Usage of DAG helps to do a lot of optimization, it can optimize and do computations in a single stage, and it also avoids unwanted reducer tasks. Spark can cache partial or complete data in memory allowing to avoid a lot of disks I/O. Commercially Spark is said to 100x faster than Hadoop.
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Apache Spark works faster when the data resides in memory, Spark processes data in memory which makes it faster in processing. While MapReduce pushes data to disk after processing it. Commercially Spark is said to 100x faster in a memory based computation and 100 times faster in a memory based computation.
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