|By Business Wire||
|June 4, 2012 12:02 PM EDT||
Algebraix Data Corporation today announced for more than 80 percent of queries, its SPARQL Server™ RDF database using an Amazon Cloud EC2 Large hardware configuration delivered an average 12-times better performance than the best results published by Revelytix.
Furthermore, Algebraix Data’s SPARQL Server is the only database to have executed all of SP2Bench queries, including all six of the queries that were not successfully executed within the Revelytix guidelines by other Resource Description Framework (RDF) databases. RDF is the standard format for encoding machine-readable information in the Semantic Web, and the SP2Bench benchmark is frequently used to gauge the relative performance of competing RDF databases.
“The outstanding SPARQL Server performance is a direct result of the algebraic techniques enabled by our patented Algebraix® technology,” said Chris Piedmonte, co-founder and CTO of Algebraix Data.
The hardware configuration used in the benchmark test was identical to the configuration used in the multivendor SP2Bench performance comparisons previously published by Revelytix, Inc. The database comprised 5M RDF triples, the largest size for which Revelytix results are available.
“While these benchmark results demonstrate the clear superiority of our Algebraix technology, they were achieved with an early prototype system, and we expect to make substantial additional functional, performance and scalability improvements prior to the official launch of our SPARQL Server product,” said Charlie Silver, CEO of Algebraix Data.
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 (10X) 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