From XML schema to relations: a cost-based approach to XML storage

As Web applications manipulate an increasing amount of XML, there is a growing interest in storing XML data in relational databases. Due to the mismatch between the complexity of XML´s tree structure and the simplicity of flat relational tables, there are many ways to store the same document in an RDBMS, and a number of heuristic techniques have been proposed. These techniques typically define fixed mappings and do not take application characteristics into account. However, a fixed mapping is unlikely to work well for all possible applications. In contrast, LegoDB is a cost-based XML storage mapping engine that explores a space of possible XML-to-relational mappings and selects the best mapping for a given application. LegoDB leverages current XML and relational technologies: (1) it models the target application with an XML Schema, XML data statistics, and an XQuery workload; (2) the space of configurations is generated through XML-Schema rewritings; and (3) the best among the derived configurations is selected using cost estimates obtained through a standard relational optimizer. We describe the LegoDB storage engine and provide experimental results that demonstrate the effectiveness of this approach