An Efficient SQL-based RDF Querying Scheme

By E. Chong, Souripriya Das, G. Eadon, Jagannathan Srinivasan. Very Large Data Bases Conference, 2005

357 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/50b302b127c4cd9e966b295ac26ebe3edd840373

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Citations in the corpus

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.”
Binary RDF representation for publication and exchange (HDT) (2013, background): “In fact, the assignment of IDs, referred to asmapping [25], is usually the first step in RDF indexing.”
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data (2009, methodology): “Using standard rewriting techniques (see [3], [17], [4]), the engine translates the query to SQL and returns the answers as computed by the underlying database engine.”
A Native and Adaptive Approach for Unified Processing of Linked Streams and Linked Data (2011, methodology): “A fair amount of work on storage and query processing for Linked Data is available, including Sesame [13], Jena [38], RISC-3X [28], YARS2 [23], and Oracle Database Semantic Technologies [16].”
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].”
The RDF-3X engine for scalable management of RDF data (2010, methodology): “, [13]) of replacing all literals by ids using a mapping dictionary.”
RDF-3X: a RISC-style engine for RDF (2008, background): “…structures and algorithms rather than supporting a wide variety of methods, 2) much lighter software footprint and overhead, and as a result, 3) simpliﬁed optimization of system internals and easier conﬁguration and self-adaptation to changing environments (e.g., data and workload characteristics).”
Scalable Semantic Web Data Management Using Vertical Partitioning (2007, background): “Oracle [22] also adopts a property table-like data structure (they call it a “subject-property matrix”) to speed up queries over RDF triples.”
Foundations of SPARQL query optimization (2008, methodology): “To give evidence for this claim, the experimental study in [19] reveals severe performance bottlenecks when evaluating complex SPARQL queries (in particular queries involving operator OPTIONAL) for both existing SPARQL implementations and state-of-the-art mapping schemes from SPARQL to SQL.”
Hexastore: sextuple indexing for semantic web data management (2008, methodology): “However , systems such as the FORTH RDF Suite [8] [9], Redland [11], Sesame [17], 3store [25] [26], Jena [46] [19] [45], DLDB [39], KAON [44], RStar [36], Oracle [20], and rdfDB [22] utilize a traditional relational databases or Berkeley DB as their underlying persistent data store [38].”