Relational Techniques for Storing and Querying RDF Data: An Overview

The Resource Description Framework (RDF) is a flexible model for representing information about resources in the Web. With the increasing amount of RDF data which is becoming available, efficient and scalable management of RDF data has become a fundamental challenge to achieve the Semantic Web vision. The RDF model has attracted attentions in the database community and many researchers have proposed different solutions to store and query RDF data efficiently. This chapter focuses on using relational query processors to store and query RDF data. It gives an overview of the different approaches and classifies them according to their storage and query evaluation strategies.

[1]  Alon Y. Halevy,et al.  Pay-as-you-go user feedback for dataspace systems , 2008, SIGMOD Conference.

[2]  Georg Lausen,et al.  An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario , 2008, SEMWEB.

[3]  Frank van Harmelen,et al.  Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema , 2002, SEMWEB.

[4]  Jeffrey Naughton,et al.  The case for a wide-table approach to manage sparse relational data sets , 2007, SIGMOD '07.

[5]  Nicholas Gibbins,et al.  3store: Efficient Bulk RDF Storage , 2003, PSSS.

[6]  Li Ma,et al.  Effective and efficient semantic web data management over DB2 , 2008, SIGMOD Conference.

[7]  Martin L. Kersten,et al.  Column-store support for RDF data management: not all swans are white , 2008, Proc. VLDB Endow..

[8]  Mohamed F. Mokbel,et al.  RDF Data-Centric Storage , 2009, 2009 IEEE International Conference on Web Services.

[9]  Georg Lausen,et al.  SP^2Bench: A SPARQL Performance Benchmark , 2008, 2009 IEEE 25th International Conference on Data Engineering.

[10]  Michael Gertz,et al.  Semantic integrity support in SQL:1999 and commercial (object-)relational database management systems , 2001, The VLDB Journal.

[11]  Atanas Kiryakov,et al.  OWLIM - A Pragmatic Semantic Repository for OWL , 2005, WISE Workshops.

[12]  Abraham Bernstein,et al.  Hexastore: sextuple indexing for semantic web data management , 2008, Proc. VLDB Endow..

[13]  Andreas Harth,et al.  Optimized index structures for querying RDF from the Web , 2005, Third Latin American Web Congress (LA-WEB'2005).

[14]  Michael Stonebraker,et al.  C-Store: A Column-oriented DBMS , 2005, VLDB.

[15]  Daniel J. Abadi,et al.  SW-Store: a vertically partitioned DBMS for Semantic Web data management , 2009, The VLDB Journal.

[16]  Jeff Heflin,et al.  DLDB: Extending Relational Databases to Support Semantic Web Queries , 2003, PSSS.

[17]  Setrag Khoshafian,et al.  A decomposition storage model , 1985, SIGMOD Conference.

[18]  James A. Hendler,et al.  The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities , 2001 .

[19]  Sherif Sakr,et al.  XQuery on SQL Hosts , 2004, VLDB.

[20]  Jeff Heflin,et al.  DLDB2: A Scalable Multi-perspective Semantic Web Repository , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[21]  Eugene Inseok Chong,et al.  An Efficient SQL-based RDF Querying Scheme , 2005, VLDB.

[22]  Toshiyuki Amagasa,et al.  A Path-based Relational RDF Database , 2005, ADC.

[23]  Jeffrey F. Naughton,et al.  Extending RDBMSs To Support Sparse Datasets Using An Interpreted Attribute Storage Format , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[24]  Gerhard Weikum,et al.  Rethinking Database System Architecture: Towards a Self-Tuning RISC-Style Database System , 2000, VLDB.

[25]  Sherif Sakr,et al.  An Experimental Evaluation of Relational RDF Storage and Querying Techniques , 2010, DASFAA Workshops.

[26]  Vassilis Christophides,et al.  The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases , 2001, SemWeb.

[27]  Gerhard Weikum,et al.  RDF-3X: a RISC-style engine for RDF , 2008, Proc. VLDB Endow..

[28]  Brian McBride,et al.  Jena: A Semantic Web Toolkit , 2002, IEEE Internet Comput..

[29]  Goetz Graefe,et al.  Sorting And Indexing With Partitioned B-Trees , 2003, CIDR.

[30]  Gerhard Weikum,et al.  Scalable join processing on very large RDF graphs , 2009, SIGMOD Conference.

[31]  Jörg Sander,et al.  PIST: An Efficient and Practical Indexing Technique for Historical Spatio-Temporal Point Data , 2008, GeoInformatica.

[32]  Tao Liu,et al.  RStar: an RDF storage and query system for enterprise resource management , 2004, CIKM '04.