| MapReduce does only batch-wise processing of data. | Apache Spark can process the data both in real-time and in batches. |
| MapReduce does SLOW processing of large data. | Apache Spark runs approximately 100 times faster than MapReduce for big data processing. |
| MapReduce stores data in HDFS (Hadoop Distributed File System) which makes it take a LONG time to GET the data. | Spark stores data in memory (RAM) which makes it easier and faster to retrieve data when needed. |
| MapReduce highly depends on disk which makes it to be a high latency framework. | Spark supports in-memory data storage and caching and makes it a low latency computation framework. |
| MapReduce requires an EXTERNAL scheduler for jobs. | Spark has its own job scheduler due to the in-memory data computation. |
