Oracle introduced partitioning as an option with Oracle8 to provide a higher degree of manageability and availability. You can take individual partitions offline for maintenance while other partitions remain available for user access. In data warehousing implementations, partitioning is sometimes used to implement rolling windows based on date ranges. Other partitioning types include hash partitioning (used to divide data into partitions using a hashing function and providing an even distribution of data) and list partitioning (enabling partitioning of data based on discrete values such as geography). Starting with Oracle Database 11g, interval partitioning can also be used to automatically create new fixed ranges as needed during data insertions. Many of these partitioning types can be used in combination as composite partitions. Examples of composite partitions in Oracle Database 11g include range-range, range-hash, range-list, list-range, list-hash, and list-list.

There are times when it is not obvious in which partition data should reside, although the partitioning key can be identified. Rather than group similar data, there are times when it is desirable to distribute data such that it does not correspond to a business or a logical view of the data, as it does in range partitioning. With hash partitioning, a row is placed into a partition based on the result of passing the partitioning key into a hashing algorithm.
Using this approach, data is randomly distributed across the partitions rather than grouped. This is a good approach for some data, but may not be an effective way to manage historical data. However, hash partitions share some performance characteristics with range partitions. For example, partition pruning is limited to equality predicates. You can also use partition-wise joins, parallel index access, and parallel DML.