Posts Tagged ‘benchmark’

SPARQL City’s Benchmark Results Showcase New Possibilities in Enterprise Graph Analytics

Solution demonstrates 10x+ the performance while running on 100x the data

Enterprise meet Graph Analysis - SPARQLcity.comNoSQL Now 2014 & SemTechBiz 2014

San Diego – August 20, 2014 – SPARQL City, which introduced its scalable graph analytic engine to market earlier this year, today announced that it has successfully run the SP2 SPARQL benchmark on 100 times the data volume as other graph solution providers, while still delivering an order of magnitude better performance on average compared to published results.

SPARQL City ran the SP2 Benchmark against 2.5 billion triples/edges on a sixteen node cluster on Amazon EC2. Average query response time for the set of seventeen queries was about 6 seconds, with query 4, the most data intensive query involving the entire dataset taking approximately 34 seconds to run. By comparison, the best reported query 4 result by other graph solution providers has been around 15 seconds, but this is when running against 25 million triples/edges, or 1/100th of the data volume in SPARQL City’s benchmark test. This level of performance, combined with the ability to easily scale out the solution on a cluster when required, makes easy to use interactive graph analytics on very large datasets possible for the first time. Detailed benchmark results can be found on our website.

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Algebraix Crushes Previous Performance Benchmark

Algebraix Data recently 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.” Read more