XML has become ubiquitous, and XML data has to be managed in databases. The current industry standard is to map XML data into relational tables and store this information in a relational database. Such mappings create both expressive power problems and performance problems. In the TIMBER [7] project we are exploring the issues involved in storing XML in native format. We believe that the key intellectual contribution of this system is a comprehensive set-at-a-time query processing ability in a

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... ative XML store, with all the standard components of relational query processing, including algebraic rewriting and a cost-based optimizer. ture of XML data, obtaining these estimates is not necessarily straightforward. We discuss effective techniques for this purpose in [8] . XML query evaluation often involves the computation of a structural join between ancestor/descendant and parent/child nodes. One has to determine the satisfaction of predicates at multiple structurally related nodes in the database. New access methods for the computation of such joins are introduced in [1, 2].