RDF Data Management Systems Based on NoSQL Databases: A Comparative Study

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-58 Number-2
Year of Publication : 2018
Authors : Mouad Banane, Abdessamad Belangour, El Houssine Labriji
DOI :  10.14445/22312803/IJCTT-V58P117

MLA

Mouad Banane, Abdessamad Belangour, El Houssine Labriji "RDF Data Management Systems Based on NoSQL Databases: A Comparative Study". International Journal of Computer Trends and Technology (IJCTT) V58(2):98-102, April 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
The growth of data transiting the Web has presented new challenges for RDF data management systems with respect to storage and the ability to effectively query these large quantities of RDF data. The limitations of traditional relational database systems and the development of NoSQL systems that are distributed databases that are scalable and tolerant fail. All these reasons motivated researchers to work on this topic to develop a system that can efficiently handle large RDF data based on NoSQL technology. This paper provides an overview on the voluminous RDF data management systems using NoSQL databases. It studies and evaluates these databases RDF (called triplestore). The comparison is based on some criteria of database software such as the NoSQL database, and model of database, index structure, database licence. This is a comparison of the systems proposed for efficient storage of massive RDF data.

Reference
[1] Khadilkar, V., Kantarcioglu, M., Thuraisingham, B., & Castagna, P. (n.d.). /home/vaibhav/Research/Jena-HBase/Results/LUBM/Query-Time-TDB-Comp-Q10.eps, (ii), 1–4
[2] Gu, R., Hu, W., & Huang, Y. (2015). Rainbow: A distributed and hierarchical RDF triple store with dynamic scalability. Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014, 561–566. http://doi.org/10.1109/BigData.2014.7004274
[3] Punnoose, R., Crainiceanu, A., & Rapp, D. (2012). Rya: a scalable RDF triple store for the clouds. Proceedings of the 1st International Workshop on Cloud Intelligence, 4. http://doi.org/10.1145/2347673.2347677
[4] Papailiou, N., Konstantinou, I., Tsoumakos, D., & Koziris, N. (2012). H RDF : Adaptive Query Processing on RDF Data in the. Proceedings of the 21st International Conference Companion on World Wide Web, 397–400. http://doi.org/10.1145/2187980.2188058
[5] Um, J. H., Lee, S., Kim, T. H., Jeong, C. H., Song, S. K., & Jung, H. (2016). Distributed RDF store for efficient searching billions of triples based on Hadoop. Journal of Supercomputing, 72(5), 1825–1840. http://doi.org/10.1007/s11227-016-1670-6
[6] Haque, A., & Perkins, L. (2012). Distributed RDF Triple Store Using HBase and Hive.
[7] Sun, J., & Jin, Q. (2010). Scalable RDF store based on HBase and MapReduce. ICACTE 2010 - 2010 3rd International Conference on Advanced Computer Theory and Engineering, Proceedings, 1, 633–636. http://doi.org/10.1109/ICACTE.2010.5578937
[8] Aswamenakul, C., & Buranarach, M. (n.d.). A Review and Design of Framework for Storing and Querying RDF Data using NoSQL Database, 1–4.
[9] Cudr, P., Haque, A., Harth, A., Keppmann, F. L., Miranker, D. P., Sequeda, J. F., & Wylot, M. (n.d.). NoSQL Databases for RDF : An Empirical Evaluation, 310–325.
[10] Rohloff, K., & Schantz, R. E. (n.d.). High-Performance , Massively Scalable Distributed Systems using the MapReduce Software Framework : The SHARD Triple-Store.
[11] Ladwig, G., & Harth, A. (2011). CumulusRDF: Linked data management on nested key-value stores. The 7th International Workshop on …, 30–42. Retrieved from http://iswc2011.semanticweb.org/fileadmin/iswc/Papers/Workshops/SSWS/Ladwig-et-all-SSWS2011.pdf
[12] Zablocki, J. (n.d.). Couchbase essentials : harness the power of Couchbase to build flexible and scalable applications.
[13] Harris, S., Lamb, N., & Shadbolt, N. (2009). 4store: The design and implementation of a clustered RDF store. CEUR Workshop Proceedings, 517, 94–109.
[14] Chang, F., Dean, J., Ghemawat, S., Hsieh, W. C., Wallach, D. A., Burrows, M., … Gruber, R. E. (n.d.). Bigtable: A Distributed Storage System for Structured Data. Retrieved from https://static.googleusercontent.com/media/research.google.com/fr//archive/bigtable-osdi06.pdf
[15] MahmoudiNasab, H., & Sakr, S. (2012). AdaptRDF: adaptive storage management for RDF databases. International Journal of Web Information Systems, 8(2), 234–250. http://doi.org/10.1108/17440081211241978

Keywords
Semantic Web, RDF, NoSQL, Big Data, SPARQL.