Partitioning breaks up data into smaller containers versus one large container. Partitioning can be leveraged for making large data sets more manageable (i.e. rolling off a whole month's data at time versus deleting data. (DML operations versus DDL operations). Performance of SQL statements increase due to table data partitioned according to how data will be retrieved. ( i.e. data in billing system uses dates and reports have where clause like where date1 between some_date and another_date. Here partition pruning or oracle knows based on the table is partitioned what partitions are needed and reduces the amount of data to search through.