Many applications require that large amounts of data are deleted from a database - typically, such bulk deletes are carried out periodically and involve old or out-of-date data. If the data is not partitioned in such a way that bulk deletes can be carried out by simply deleting whole partitions, then most current database products execute such bulk delete operations very poorly. The reason is that every record is deleted from each index individually. This paper proposes and evaluates a new class of techniques to support bulk delete operations more efficiently. These techniques outperform the "record-at-a-time" approach implemented in many database products by about an order of magnitude.