Evaluating Performance and Quality of XML-Based Similarity Joins
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
EXsum: an XML summarization framework
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
Usage-driven storage structures for native XML databases
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
S3: Evaluation of tree-pattern XML queries supported by structural summaries
Data & Knowledge Engineering
The promise of solid state disks: increasing efficiency and reducing cost of DBMS processing
C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering
A cluster-based approach to XML similarity joins
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Essential Performance Drivers in Native XML DBMSs
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Key concepts for native XML processing
From active data management to event-based systems and more
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Because XML documents tend to be very large, are accessed by declarative and navigational languages, and often are processed in a collaborative way using read/write transactions, their fine-grained storage and management in XML DBMSs is a must for which, in turn, a flexible and space-economic tree representation is mandatory. In this paper, we explore a variety of options to natively store, encode, and compress XML documents thereby preserving the full DBMS processing flexibility on the documents required by the various language models and usage characteristics. Important issues of our empirical study are related to node labeling, document container layout, indexing, as well as structure and content compression. Encoding and compression of XML documents with their complete structure leads to a space consumption of ~40% to ~60% compared to their plain representation, whereas structure virtualization (elementless storage) saves in the average more than 10%, in addition.