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A Survey on RDF Data Store Based on NoSQL Systems for the Semantic Web Applications

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Advanced Intelligent Systems for Sustainable Development (AI2SD’2018) (AI2SD 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 915))

Abstract

Today the Resource Description Framework (RDF) that allows computers to understand and exploit Web data becomes very much in a progressive way, as well as the amount of web data that becomes very large. The storage and efficient management of this large RDF data is a real challenge in front of the classic RDF databases called triplestore. Recently, several researches focus on storing RDF data in triplestores based on NoSQL data management systems like HBase, Cassandra, Accumulo, and Couchbase. The majority of these researches are based on HBase. This NoSQL technology that is intended to handle this phenomenon of data explosion called Big Data, provided benefits like scalability and high availability compared to traditional triplestores. In this paper, we review existing works and systems that use NoSQL databases to store massive RDF data.

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References

  1. Mnola, F., Miller, E., McBride, B.: RDF Primer. W3C Recommendation 10(1–107), 6 (2004)

    Google Scholar 

  2. Sequeda, J.F., Miranker, D.P.: Ultrawrap: SPARQL Execution on Relational Data. 13

    Google Scholar 

  3. Aasman, J.: Allegro Graph: RDF Triple Database

    Google Scholar 

  4. Harris, S., Lamb, N., Shadbolt, N.: 4store: the design and implementation of a clustered RDF store. In: CEUR Workshop Proceedings, vol. 517, pp. 94–109 (2009)

    Google Scholar 

  5. Virtuoso Erling, O., Mikhailov, I.: RDF Support in the Virtuoso DBMS, pp. 7–24. Springer, Heidelberg (2009)

    Google Scholar 

  6. Ladwig, G., Harth, A.: CumulusRDF: Linked Data Management on Nested Key-Value Stores. 13 (2011)

    Google Scholar 

  7. Khadilkar, V., Kantarcioglu, M., Thuraisingham, B., Castagna, P.: Jena-HBase: A Distributed, Scalable and Efficient RDF Triple Store. 4

    Google Scholar 

  8. Punnoose, R., Crainiceanu, A., Rapp, D.: Rya: A Scalable RDF Triple Store for the Clouds (2012)

    Google Scholar 

  9. https://pig.apache.org/. Apache Pig. Accessed 05 June 2018

  10. https://zookeeper.apache.org/. Apache ZooKepper. Accessed 07 July 2016

  11. https://ambari.apache.org/. Apache Ambari. Accessed 21 June 2018

  12. https://mahout.apache.org/. Apache Mahout

  13. Klophaus, R., Rusty: Riak core. In: ACM SIGPLAN Commercial Users of Functional Programming (CUFP’10), p. 1 (2010)

    Google Scholar 

  14. Redis in Action. (n.d.). Retrieved 21 Jan 2018, from https://dl.acm.org/citation.cfm?id=2505464

  15. http://www.project-voldemort.com/voldemort/. Accessed 28 June 2018

  16. Apache HBase—Apache HBaseTM Home. https://hbase.apache.org/. Accessed 18 July 2018

  17. Brown, M.: Learning Apache Cassandra : Build an Efficient, Scalable, Fault-Tolerant, and Highly-Available Data Layer into Your Application Using Cassandra (n.d.)

    Google Scholar 

  18. Anderson, J.C., Lehnardt, J., Slater, N.: CouchDB : The Definitive Guide. O’Reilly Media, Inc (2010)

    Google Scholar 

  19. Chodorow, K.: (n.d.). MongoDB : The Definitive Guide

    Google Scholar 

  20. Vukotic, A., Watt, N., Abedrabbo, T., Fox, D., Partner, J.: (n.d.). Neo4j in Action

    Google Scholar 

  21. Iordanov, B.: HyperGraphDB: A Generalized Graph Database, pp. 25–36. Springer, Heidelberg (2010)

    Google Scholar 

  22. Pointer, R., Kallen, N., Ceaser, E., Kalucki, J.: Introducing FlockDB

    Google Scholar 

  23. Sun, J., Jin, Q.: Scalable RDF store based on HBase and MapReduce, Aug 2010

    Google Scholar 

  24. Haque, A., Perkins, L.: Distributed RDF Triple Store Using HBase and Hive. 4

    Google Scholar 

  25. https://hive.apache.org/. Apache Hive. Accessed 18 July 2018

  26. Gu, R., Hu, W., Huang, Y.: Rainbow: A Distributed and Hierarchical RDF Triple Store With Dynamic Scalability, Oct 2014

    Google Scholar 

  27. Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: a distributed storage system for structured data. ACM Trans. Comput. Syst. 26, 1–26 (2008)

    Article  Google Scholar 

  28. http://hadoop.apache.org/. Apache Hadoop. Accessed 11 June 2018

  29. https://accumulo.apache.org/. Apache Accumulo. Accessed 27 June 2018

  30. Papailiou, N., Konstantinou, I., Tsoumakos, D., Koziris, N.: H2RDF: Adaptive Query Processing on RDF Data in the Cloud (2012)

    Google Scholar 

  31. Choi, H., Son, J., Cho, Y., Sung, M.K., Chung, Y.D.: SPIDER: A System for Scalable, Parallel/Distributed Evaluation of Large-scale RDF Data (2009)

    Google Scholar 

  32. Cudré-Mauroux, P., Enchev, I., Fundatureanu, S., Groth, P., Haque, A., Harth, A., Keppmann, F.L., Miranker, D., Sequeda, J.F., Wylot, M.: NoSQL databases for RDF: an empirical evaluation. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., and Janowicz, K. (eds.): The Semantic Web—ISWC 2013, pp. 310–325. Springer, Heidelberg (2013)

    Google Scholar 

  33. Brown, M.C.: Getting Started with Couchbase Server. Oreilly (2012)

    Google Scholar 

  34. https://mahout.apache.org/. Apache Mahout. Accessed 06 June 2018

  35. Sch, A., Przyjaciel-zablocki, M., Skilevic, S., Lausen, G.: S2RDF : RDF Querying with SPARQL on Spark, pp. 804–815 (n.d.)

    Google Scholar 

  36. https://spark.apache.org/. Apache Spark. Accessed 09 June 2018

  37. Sch, A., Przyjaciel-zablocki, M., Hornung, T., Lausen, G.: PigSPARQL : A SPARQL Query Processing Baseline for Big Data (n.d.)

    Google Scholar 

  38. Banane, M., Belangour, A., Houssine, L.E.: Storing RDF data into big data NoSQL databases. In: Lecture Notes in Real-Time Intelligent Systems, pp. 69–78. Springer, Cham (2017)

    Google Scholar 

  39. Banane, M., Belangour, A., Labriji, E.H.: RDF data management systems based on NoSQL databases: a comparative study. Int. J. Comput. Trends Technol. (IJCTT) V58(2), 98–102 (2018)

    Google Scholar 

  40. Guo, Y., Pan, Z., Heflin, J.: LUBM: A benchmark for OWL knowledge base systems. J. Web Sem. 3(2–3), 158–182 (2005)

    Article  Google Scholar 

  41. Erraissi, A., Belangour, A., Tragha, A.: A Big data Hadoop building blocks comparative study. Int. J. Comput. Trends Technol. Accessed 18 June 2017

    Google Scholar 

  42. Erraissi, A., Belangour, A., Tragha, A.: A comparative study of hadoop-based big data architectures. Int. J. Web Appl. IJWA 9(4) (2017)

    Google Scholar 

  43. Erraissi, A., Belangour, A., Tragha, A.: Digging into hadoop based big data architectures. Int. J. Comput. Sci. Issues IJCSI 14(6), 52–59 (2017)

    Article  Google Scholar 

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Authors and Affiliations

  1. Hassan 2 University, Casablanca, Morocco

    Mouad Banane & Abdessamad Belangour

Authors
  1. Mouad Banane
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  2. Abdessamad Belangour
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Correspondence to Mouad Banane .

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Editors and Affiliations

  1. Faculty of Sciences and Techniques, Abdelmalek Essaâdi University, Tangier, Morocco

    Mostafa Ezziyyani

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Banane, M., Belangour, A. (2019). A Survey on RDF Data Store Based on NoSQL Systems for the Semantic Web Applications. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-11928-7_40

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