RDD stands for Resilient Distributed Dataset (RDD). It is a data structure that stores immutable objects. It supports the storage of objects of any language, like Python, Java, Scala, and other user-defined objects. MapReduce is used for massively parallel processing of data quickly. Spark uses RDD to perform MapReduce operations. RDDs can be created in 2 ways: either by parallelising a data set in your system or by referencing an external data storage system. RDD is fault-tolerant and supports parallel processing. It is mainly used to process and manipulate unstructured data. RDD is a distributed system. It follows the Lazy Evaluation Principle, i.e. transformations are applied only when we call it and not when the data is loaded.