The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases

By S. Alexaki, V. Christophides, G. Karvounarakis, Dimitris Plexousakis, Karsten Tolle. International Workshop on the Semantic Web, 2001

303 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2e0fba2ac049e77e7dd04f3844918e93485dda22

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Citations in the corpus

Hexastore: sextuple indexing for semantic web data management (2008, methodology): “Thus, significant efforts have been dedicated to the development of architectures for storing and querying RDF data, called triple stores [8] [9] [11] [17] [25] [26] [46] [19] [45] [39] [44].”
Scalable SPARQL querying of large RDF graphs (2011, background): “RDFSuite [7], and continued through many new systems that have been proposed in the last few years [12, 4, 24, 32, 29, 25, 15].”
A Distributed Graph Engine for Web Scale RDF Data (2013, methodology): “We conduct comprehensive experimental studies on real life, web scale RDF data to demonstrate the effectiveness of our approach.”
RDF-3X: a RISC-style engine for RDF (2008, background): “Most publicly accessible RDF systems have mapped RDF triples onto relational tables (e.g., RDFSuite [2, 32], Sesame [8, 28], Jena [23, 46], the C-Store-based RDF engine of [1], and also Oracle’s RDF MATCH implementation [11]).”
Jena: implementing the semantic web recommendations (2004, unknown): “A property table (also known as attribute tables [1]) holds statements for a specific property.”
The RDF-3X engine for scalable management of RDF data (2010, background): “Most publicly accessible RDF systems have mapped RDF triples onto relational tables (e.g., RDFSuite [2] [44], Sesame [8] [39], Jena [26] [63], the C-Store-based RDF engine of [1], and also Oracle's RDF MATCH implementation [12] ).”
RQL: a declarative query language for RDF (2002, background): “Readers are referred to [6] for a detailed presentation of the system architecture and components.”
The Internet of Things: A Survey from the Data-Centric Perspective (2013, unknown): “In these cases, giant triples tables are used in order to represent the underlying RDF data [11, 12, 18, 24, 49, 50, 85, 113, 114].”
SW-Store: a vertically partitioned DBMS for Semantic Web data management (2009, methodology): “We propose storage of RDF data using a fully decomposed storage model (DSM) [20], a performance enhancing technique that has proven to be useful in a variety of applications including data warehousing [2], biomedical data [21], and in the context of RDF/S, for taxonomic data [9,47].”
Scalable Semantic Web Data Management Using Vertical Partitioning (2007, methodology): “We propose storage of RDF data using a fully decomposed storage model (DSM) [24], a performance enhancing technique that has proven to be useful in a variety of applications including data warehousing [13], biomedical data [25], and interestingly, in the context of RDF/S, for taxonomic data [17, 32]”