Triplestore
A triplestore is a purpose-built database for the storage and retrieval of triples,[1] a triple being a data entity composed of subject-predicate-object, like "Bob is 35" or "Bob knows Fred".
Much like a relational database, one stores information in a triplestore and retrieves it via a query language. Unlike a relational database, a triplestore is optimized for the storage and retrieval of triples. In addition to queries, triples can usually be imported/exported using Resource Description Framework (RDF) and other formats.
Some triplestores can store billions of triples.[2] The performance of a particular triplestore can be measured with the Lehigh University Benchmark (LUBM),[3] or with real data from UniProt.
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[edit] Implementation
Some triplestores have been built as database engines from scratch, while others have been built on top of existing commercial relational database engines (i.e. SQL-based).[4] Like the early development of OLAP databases, this intermediate approach allowed large and powerful database engines to be constructed for little programming effort in the initial phases of triplestore development. Long-term though it seems likely that native triplestores will have the advantage for performance. A difficulty with implementing triplestores over SQL is that although "triples" may thus be "stored", implementing efficient querying of a graph-based RDF model (i.e. mapping from SPARQL) onto SQL queries is difficult.[5]
[edit] List of triplestore implementations
[edit] See also
- Freebase, uses a triplestore called graphd.[6]
- Named graphs
[edit] References
- ^ TripleStore, Jack Rusher, Semantic Web Advanced Development for Europe (SWAD-Europe), Workshop on Semantic Web Storage and Retrieval - Position Papers
- ^ Tom Ilube (2007-11-30), Semantic Technologies Really Do Pay Off, Semantic Universe, http://www.semanticuniverse.com/articles-semantic-technologies-really-do-pay.html
- ^ Lehigh University Triplestore Benchmark
- ^ US 2003145022 Storage and Management of Semi-structured Data (Use of SQL relational databases as an RDF triple store), 2003
- ^ Broekstra, Jeen (19 September, 2007). "The importance of SPARQL can not be overestimated". http://www.semantic-web.at/1.36.resource.90.jeen-broekstra-x22-the-importance-of-sparql-can-not-be-overestimated-x22.htm.
- ^ "a-brief-tour-of-graphd". http://blog.freebase.com/2008/04/09/a-brief-tour-of-graphd/. Retrieved 2009-07-08.
[edit] External links
- A list of large triplestores
- Lehigh University Benchmark (LUBM)
- Semantic Systems Biology
- ARC's RDF Store is built using PHP with MySQL as the backend for the triplestore. It also provides a SPARQL endpoint for access and updating of stored triples.
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