GraphDB-SE is the commercial edition of GraphDB -- a high-performance semantic repository created by Ontotext. It is implemented in Java and packaged as a Storage and Inference Layer (SAIL) for the Sesame RDF framework. GraphDB-SE is a native RDF rule-entailment and storage engine. The supported semantics can be configured through rule-set definition and selection. Included are rule-sets for OWL-Horst, unconstrained RDFS with OWL Lite and the OWL2 profiles RL and QL. Custom rule-sets allow tuning for optimal performance and expressivity.
Reasoning and query evaluation are performed over a persistent storage layer. Loading, reasoning and query evaluation proceed extremely quickly even against huge ontologies and knowledge bases.
GraphDB-SE can manage billions of explicit statements on desktop hardware and can handle tens of billions of statements on commodity server hardware. According to public evaluation data, GraphDB-SE is the most scalable OWL repository currently available.
GraphDB's web site, [http://ontotext.com/products/ontotext-graphdb/|http://ontotext.com/products/ontotext-graphdb/], provides extensive information and references regarding support contacts and mailing lists, documentation and latest performance benchmarks.
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h1. Features
The key features of the current release of GraphDB-SE can be summarised as follows:
* *The most scalable semantic repository* in the World, both in terms of the volume of RDF data it can store and the speed with which it can load and do inferencing;
* *Pure Java implementation*, ensuring ease of deployment and portability;
* Compatible with *Sesame 2*, which brings interoperability benefits and support for all major RDF syntaxes and query languages;
* Compatible with [Jena|http://jena.sourceforge.net/] with a built-in adapter layer;
* *Customisable reasoning,* in addition to RDFS, OWL-Horst, and OWL 2 RL support;
* *Optimised owl:sameAs* handling, which delivers dramatic improvements in performance and usability when huge volumes of data from multiple sources are integrated.
* *Clustering support* brings resilience, fail-over and scalable parallel query processing;
* *Geo-spatial extensions* for special handling of 2-dimensional spherical data allowing data using the WGS84 RDF vocabulary to be indexed and processed quickly using a variety of special geometrical query constructions and SPARQL extensions functions;
* *Full-text search* support, based on either Lucene or proprietary search techniques;
* *High performance retraction* of statements and their inferences -- so inference materialisation speeds up retrieval, but without delete performance degradation;
* Powerful and expressive *consistency/integrity constraint checking* mechanisms;
* *RDF rank*, similar to Google's PageRank, can be calculated for the nodes in an RDF graph and used for ordering *query results by relevance*, visualisation and any other purposes;
* *RDF Priming*, based upon activation spreading, allows efficient data selection and context-aware query answering for handling huge datasets;
* *Notification* mechanism, to allow clients to react to statements in the update stream.
* *Lucene connector* \- provides extremely fast normal and facet (aggregation) searches; has the additional benefit to stay automatically up-to-date with the GraphDB repository data.
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