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What is the key difference between Apache Spark and MapReduce?

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Following is the list of main differences between Apache Spark and MapReduce:

Comparison Parameter Apache Spark MapReduce
Data processing: Apache Spark can process data in batches as well as in real-time. MapReduce can process data in batches only.
Speed: The processing speed of Apache Spark is extremely high. It runs almost 100 times faster than Hadoop MapReduce. Hadoop MapReduce is slower than Apache Spark in the case of large scale data processing.
Data Storage: Apache Spark stores data in the RAM, i.e., in-memory. It is easier to retrieve it, and that's why it is best to use in Artificial Intelligence. Hadoop MapReduce stores data in HDFS. So, it takes a long time to retrieve the data from there.
Caching: Apache Spark provides caching and in-memory data storage. Hadoop MapReduce is highly disk-dependent.

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