Ali, W.; Saleem, M.; Bin, Y.; Hogan, A.; Ngomo, A.N. A Survey of RDF Stores & SPARQL Engines for Querying Knowledge Graphs. Preprints2021, 2021040199. https://doi.org/10.20944/preprints202104.0199.v1
APA Style
Ali, W., Saleem, M., Bin, Y., Hogan, A., & Ngomo, A.N. (2021). A Survey of RDF Stores & SPARQL Engines for Querying Knowledge Graphs. Preprints. https://doi.org/10.20944/preprints202104.0199.v1
Chicago/Turabian Style
Ali, W., Aidan Hogan and A.-C. Ngonga Ngomo. 2021 "A Survey of RDF Stores & SPARQL Engines for Querying Knowledge Graphs" Preprints. https://doi.org/10.20944/preprints202104.0199.v1
Abstract
Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graph-based data model has seen ever-broadening adoption, particularly on the Web. This adoption has prompted the standardization of the SPARQL query language for RDF, as well as the development of a variety of local and distributed engines for processing queries over RDF graphs. These engines implement a diverse range of specialized techniques for storage, indexing, and query processing. A number of benchmarks, based on both synthetic and real-world data, have also emerged to allow for contrasting the performance of different query engines, often at large scale. This survey paper draws together these developments, providing a comprehensive review of the techniques, engines and benchmarks for querying RDF knowledge graphs.
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.