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.
Keywords
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Mnola, F., Miller, E., McBride, B.: RDF Primer. W3C Recommendation 10(1–107), 6 (2004)
Sequeda, J.F., Miranker, D.P.: Ultrawrap: SPARQL Execution on Relational Data. 13
Aasman, J.: Allegro Graph: RDF Triple Database
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)
Virtuoso Erling, O., Mikhailov, I.: RDF Support in the Virtuoso DBMS, pp. 7–24. Springer, Heidelberg (2009)
Ladwig, G., Harth, A.: CumulusRDF: Linked Data Management on Nested Key-Value Stores. 13 (2011)
Khadilkar, V., Kantarcioglu, M., Thuraisingham, B., Castagna, P.: Jena-HBase: A Distributed, Scalable and Efficient RDF Triple Store. 4
Punnoose, R., Crainiceanu, A., Rapp, D.: Rya: A Scalable RDF Triple Store for the Clouds (2012)
https://pig.apache.org/. Apache Pig. Accessed 05 June 2018
https://zookeeper.apache.org/. Apache ZooKepper. Accessed 07 July 2016
https://ambari.apache.org/. Apache Ambari. Accessed 21 June 2018
https://mahout.apache.org/. Apache Mahout
Klophaus, R., Rusty: Riak core. In: ACM SIGPLAN Commercial Users of Functional Programming (CUFP’10), p. 1 (2010)
Redis in Action. (n.d.). Retrieved 21 Jan 2018, from https://dl.acm.org/citation.cfm?id=2505464
http://www.project-voldemort.com/voldemort/. Accessed 28 June 2018
Apache HBase—Apache HBaseTM Home. https://hbase.apache.org/. Accessed 18 July 2018
Brown, M.: Learning Apache Cassandra : Build an Efficient, Scalable, Fault-Tolerant, and Highly-Available Data Layer into Your Application Using Cassandra (n.d.)
Anderson, J.C., Lehnardt, J., Slater, N.: CouchDB : The Definitive Guide. O’Reilly Media, Inc (2010)
Chodorow, K.: (n.d.). MongoDB : The Definitive Guide
Vukotic, A., Watt, N., Abedrabbo, T., Fox, D., Partner, J.: (n.d.). Neo4j in Action
Iordanov, B.: HyperGraphDB: A Generalized Graph Database, pp. 25–36. Springer, Heidelberg (2010)
Pointer, R., Kallen, N., Ceaser, E., Kalucki, J.: Introducing FlockDB
Sun, J., Jin, Q.: Scalable RDF store based on HBase and MapReduce, Aug 2010
Haque, A., Perkins, L.: Distributed RDF Triple Store Using HBase and Hive. 4
https://hive.apache.org/. Apache Hive. Accessed 18 July 2018
Gu, R., Hu, W., Huang, Y.: Rainbow: A Distributed and Hierarchical RDF Triple Store With Dynamic Scalability, Oct 2014
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)
http://hadoop.apache.org/. Apache Hadoop. Accessed 11 June 2018
https://accumulo.apache.org/. Apache Accumulo. Accessed 27 June 2018
Papailiou, N., Konstantinou, I., Tsoumakos, D., Koziris, N.: H2RDF: Adaptive Query Processing on RDF Data in the Cloud (2012)
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)
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)
Brown, M.C.: Getting Started with Couchbase Server. Oreilly (2012)
https://mahout.apache.org/. Apache Mahout. Accessed 06 June 2018
Sch, A., Przyjaciel-zablocki, M., Skilevic, S., Lausen, G.: S2RDF : RDF Querying with SPARQL on Spark, pp. 804–815 (n.d.)
https://spark.apache.org/. Apache Spark. Accessed 09 June 2018
Sch, A., Przyjaciel-zablocki, M., Hornung, T., Lausen, G.: PigSPARQL : A SPARQL Query Processing Baseline for Big Data (n.d.)
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)
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)
Guo, Y., Pan, Z., Heflin, J.: LUBM: A benchmark for OWL knowledge base systems. J. Web Sem. 3(2–3), 158–182 (2005)
Erraissi, A., Belangour, A., Tragha, A.: A Big data Hadoop building blocks comparative study. Int. J. Comput. Trends Technol. Accessed 18 June 2017
Erraissi, A., Belangour, A., Tragha, A.: A comparative study of hadoop-based big data architectures. Int. J. Web Appl. IJWA 9(4) (2017)
Erraissi, A., Belangour, A., Tragha, A.: Digging into hadoop based big data architectures. Int. J. Comput. Sci. Issues IJCSI 14(6), 52–59 (2017)
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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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DOI: https://doi.org/10.1007/978-3-030-11928-7_40
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