Storage and retrieval of XML data using relational databases

Abstract

The Extensible Markup Language (XML) is becoming the dominant standard for exchanging data over World Wide Web. Due to its flexibility, XML is rapidly emerging as the de facto standard for exchanging and querying documents on the Web to the next generation web applications including electronic commerce and intelligent web searching. XML documents can be stored and queried by using specialized semistructure repositories. While this is a viable approach to handle XML data, these specialized systems are yet premature since the semistructure data research itself is still young. Furthermore, it does not allow us to use the state-of-the-art relational database technologies available today that have been developed and tuned for last decades. Not only that, large volumes of data available today generally exist in relational database systems. Therefore, efficient storage and retrieval of native XML data and existing relational data seamlessly is becoming important. In fact, all major commercial relational vendors are working hard to support such capabilities and to build an infrastructure to enable them. However, they face the following three challenges: (1) how to represent XML data in relational model, (2) how to support XML query’s processing over XML data stored in relational databases, and (3) how to publish existing relational data to XML format. We will discuss current state of the art technologies for these challenges and present the future research issues. Surajit Chaudhuri is a senior researcher and manager of the DataManagement, Exploration and Mining Group at Microsoft Research. He has worked extensively in the area of self-tuning database technology, query processing, data warehousing and data mining on SQL systems. He has published many papers in leading database conferences and journals. His work on self-tuning database technology and data mining has been incorporated in the Microsoft SQL Server product. Surajit has been a member of program committees of leading database and data mining conferences. In 1999, he was the co-chair of the ACM International Conference on Knowledge Discovery and Data Mining and co-chair of the industrial track of the ACM SIGMOD conference. Surajit did his Ph.D. from Stanford University and B.Tech from Indian Institute of Technology (Kharagpur, India). Prior to joining Microsoft Research, he was a member of the research staff at Hewlett-Packard Laboratories (Palo Alto) from 1992-1995