XRel: a path-based approach to storage and retrieval of XML documents using relational databases
ACM Transactions on Internet Technology (TOIT)
Efficient Relational Storage and Retrieval of XML Documents
Selected papers from the Third International Workshop WebDB 2000 on The World Wide Web and Databases
XISS/R: XML indexing and storage system using RDBMS
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
PIVOT and UNPIVOT: optimization and execution strategies in an RDBMS
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Pivoted table index for querying product-property-value information
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Pivoting approaches for bulk extraction of Entity-Attribute-Value data
Computer Methods and Programs in Biomedicine
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In order to support corporate business' competition on speed to market for product and service development, generically modeled data structures have been widely used in the development of vertical application software systems, and in storing XML and RDF data for its flexibility, adaptability, and agility. However, generic data models require multiple self-joins on a single table with a large volume of data, causing slow performance for business intelligence (BI) applications. On the other hand, shredded XML data stored in traditional specific data models have faster performance but are not flexible, adaptive, or agile for speed to market. A generic data model named the Class Object Value Element Relationship (COVER) model was developed for storing node-oriented tree data information, and is suitable for automated pivot view generation and distributed data processing. This approach utilizes pivot views with appropriate metadata constructs to expose the search predicate fields for indexing and results in performance gains in data retrieval from branches or leaves across multiple trees for production support or data retrieval to feed business intelligence and data mining. Benchmark experiments for comparing the query performance on the COVER model against self-join and XPath/XQuery approaches using RDBMS were executed and proved that the COVER model outperforms the other two on the same sets of test data queries.