Path Materialization Revisited: An Efficient Storage Model for XML Data

XML is emerging as a new major standard for representing data on the world wide web. Several XML storage models have been proposed to store XML data in different database management systems. The unique feature of model-mappingbased approaches is that no DTD information is required for XML data storage. In this paper, we present a new modelmapping-based storage model, called XParent. Unlike the existing work on model-mapping-based approaches that emphasized on converting XML documents to/from database schema and translation of XML queries into SQL queries, in this paper, we focus ourselves on the effectiveness of storage models in terms of query processing. We study the key issues that affect query performance, namely, storage schema design (storing XML data across multiple tables) and path materialization (storing path information in databases). We show that similar but different storage models significantly affect query performance. A performance study is conducted using three data sets and query sets. The experimental results are presented.