AUSTIN, Texas--(BUSINESS WIRE)--Algebraix Data Corporation today announced its SPARQL Server™ RDF database is executing the SP2Bench benchmark more than three times faster than reported in June 2012. The dramatic performance improvement is made possible by an algebraic query optimizer that is able to reuse work performed to answer prior queries.
Furthermore, SPARQL Server’s Resource Description Framework (RDF) load performance has improved significantly, loading 384,000 triples per second from one file on a workstation class system. This is more than five times faster than June’s performance and is several times faster than any current vendor published results for loading triples from one file.
“The outstanding SPARQL Server performance is a direct result of the algebraic techniques enabled by our patented Algebraix technology,” said Arthur Keen, VP of strategy and products at Algebraix Data. “SPARQL Server is the only data-management system with the flexibility and performance to help enterprises embrace Big Data and semantics without heavy integration work retrofitting their existing IT infrastructures.”
With SPARQL Server, enterprises can fuse Big Data, relational data and semantic data into a high-performance analytic environment that is both dynamic and distributed. SPARQL Server bridges the great data divide and gives enterprises long-sought simplicity. Now enterprises can leverage all of their existing data and applications and combine them with new data and applications, as they emerge, without advance modeling or tuning and without regard to structure or location.
About Algebraix Data Corporation
Algebraix Data Corporation is enabling Web 3.0 for the enterprise with SPARQL Server™, a high-speed RDF database that provides concurrent access to semantic, relational and Big Data. Revolutionary performance and self-optimization features are made possible by rigorous proprietary mathematics inside patented ALGEBRAIX® technology. With this radical advancement in data management, enterprises can get maximum value from private and public data in real-time and regardless of its structure or location. For more information, visit: www.algebraixdata.com