RIQ: Fast Processing of SPARQL Queries on RDF Quadruples

Katib, Anas; Slavov, Vasil; Rao, Praveen

doi:10.2139/ssrn.3199230

“…The RIQ system [100] rather proposes a custom index for quads called a PV-index. The system specifically focuses on the problem of finding (named) graphs that match a BGP.…”

Section: Quad Indexesmentioning

confidence: 99%

“…RIQ [100] (2016) provides a layer on top of an existing RDF store that indexes similar named graphs in a SPARQL dataset. A bit vector -called a "pattern vector" -is computed for each named graph in the dataset.…”

Section: Rq-rdf-3x [113] (mentioning

confidence: 99%

A survey of RDF stores & SPARQL engines for querying knowledge graphs

Ali

¹

,

Saleem

²

,

Yao

³

et al. 2021

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Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graphbased 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.

show abstract

“…Query Pr. T Q V P G M T Q E P N J S M P M W N R Q RedLand [22] 2001 ✓ ✓ Jena [128] 2002 ✓ ✓ ✓ ✓ RDF4J [34] 2002 ✓ ✓ ✓ ✓ ✓ RSSDB [97,98] 2002 ✓ ✓ ✓ ✓ 3store [74] 2003 [45,46] 2004 [121] 2004 ✓ ✓ ✓ ✓ BRAHMS [90] 2005 ✓ ✓ ✓ GraphDB [105,26] 2005 [179] 2006 ✓ ✓ ✓ ✓ ✓ Virtuoso [54] 2006 ✓ ✓ ✓ ✓ ✓ ✓ GRIN [194] 2007 ✓ ✓ ✓ SW-Store [1] 2007 ✓ Blazegraph [190] 2008 ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Hexastore [201] 2008 ✓ ✓ ✓ ✓ RDF-3X [142] 2008 ✓ ✓ ✓ ✓ ✓ BitMat [15] 2009 ✓ ✓ ✓ ✓ DOGMA [33] 2009 ✓ ✓ ✓ ✓ LuposDate [61] 2009 ✓ ✓ ✓ Parliament [106] 2009 [223] 2011 ✓ ✓ ✓ ✓ SpiderStore [138] 2011 ✓ ✓ SAINT-DB [154] 2012 [191] 2013 [11] 2015 ✓ ✓ ✓ RDFCSA [32,31] 2015 ✓ ✓ ✓ RDFox [138] 2015 ✓ ✓ ✓ ✓ ✓ Turbo HOM++ [102] 2015 ✓ ✓ ✓ RIQ [100] 2016 ✓ ✓ ✓ ✓ ✓ axonDB [131] 2017 ✓ ✓ ✓ ✓ ✓ HTStore [116] 2017 ✓ ✓ AMBER [87] 2018 ✓ Jena-LTJ [81] 2019 ✓ ✓ ✓ BMatrix [30] 2020 ✓ ✓ Tentris [24] 2020 ✓ ✓ ✓ ✓ which are additionally associated with a triple identifier. SPARQL queries are supported, where the most recent version provides an option for two query engines: SBQE, which is optimized for SPARQL 1.0-style queries, and MJQE, which features merge joins and caching techniques optimized for property paths.…”

Section: Enginementioning

confidence: 99%

A Survey of RDF Stores & SPARQL Engines for Querying Knowledge Graphs

Ali¹,

Yao²,

Hogan³

et al. 2021

Preprint

View full text Add to dashboard Cite

Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graphbased 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.

show abstract

“…RIQ [61] is based on the storage of RDF data as new vector representation. This is achieved by applying different transformations related to a triple in RDF graph and a triple pattern in a BGP.…”

Section: Centralized Rdf Enginesmentioning

confidence: 99%