The Michigan benchmark: towards XML query performance diagnostics

We propose a micro-benchmark for XML data management to aid engineers in designing improved XML processing engines. This benchmark is inherently different from application-level benchmarks, which are designed to help users choose between alternative products. We primarily attempt to capture the rich variety of data structures and distributions possible in XML, and to isolate their effects, without imitating any particular application. The benchmark specifies a single data set against which carefully specified queries can be used to evaluate system performance for XML data with various characteristics. We have used the benchmark to analyze the performance of three database systems: two native XML DBMS, and a commercial ORDBMS. The benchmark reveals key strengths and weaknesses of these systems. We find that commercial relational techniques are effective for XML query processing in many cases, but are sensitive to query rewriting, and require better support for efficiently determining i...

• Type: Journal
• Year: 2006
• Where: IS
• Authors: Kanda Runapongsa, Jignesh M. Patel, H. V. Jagadish, Yun Chen, Shurug Al-Khalifa
• Keywords: Artificial Intelligence, IS 2006, Native Xml Dbms, XML Data, XML Data Management