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Abstract. This paper describes the overall design and architecture of the Timber XML database system currently being implemented at the University of Michigan. The system is based upon a bulk algebra for manipulating trees, and natively stores XML. New access methods have been developed to evaluate queries in the XML context, and new cost estimation and query optimization techniques have also been developed. We present performance numbers to support some of our design decisions. We believe that the key intellectual contribution of this system is a comprehensive set-at-a-time query processing ability in a native XML store, with all the standard components of relational query processing, including algebraic rewriting and a cost-based optimizer.

XML databases often contain documents comprising structured text. Therefore, it is important to integrate "information retrieval style" query evaluation, which is well-suited for natural language text, with standard "database style" query evaluation, which handles structured queries efficiently. Relevance scoring is central to information retrieval. In the case of XML, this operation becomes more complex because the data required for scoring could reside not directly in an element itself but also in its descendant elements.In this paper, we propose a bulk-algebra, TIX, and describe how it can be used as a basis for integrating information retrieval techniques into a standard pipelined database query evaluation engine. We develop new evaluation strategies essential to obtaining good performance, including a stack-based TermJoin algorithm for efficiently scoring composite elements. We report results from an extensive experimental evaluation, which show, among other things, that the new TermJoin access method outperforms a direct implementation of the same functionality using standard operators by a large factor.

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