Dataframes were introduced in Spark 1.3. Dataframe built on the concept of providing schemas over the data. An RDD basically consists of raw data. Although it provides various functions to process the data, it is a collection of Java objects and is involved in the overhead of garbage collection and serialization. Also, Spark SQL concepts can only be leveraged if it contains some schema. So, earlier version of a Spark provide another version of RDD called SchemaRDD.