YarcData's Urika Shows Big Data is More than Hadoop and Data Warehouses (Carl Claunch, Sept 11, 2012)
- Why data discovery is hard
- Analyst validation
- Discover unknown linkages
- Purpose built
- The power of graph analytics
- What fits into 512 TBs?
- Easy to deploy
Easy to deploy into your existing analytical infrastructureYou want to perform big data discovery…not build a big data discovery engine.
We get it. That’s why we built our Urika data discovery solution as an appliance. We’ve already built the discovery engine that’s right for big data. We’ve already architected the large, high-performance memory, extreme processing power, and massive multi-threading required to surface data relationships and patterns from massive amounts of diverse data sources.
We’ve already integrated our powerful purpose-built hardware with a software stack that knows how to get every cycle out of it for the real time performance demanded by big data discovery. Our graph analytic database is tuned specifically to fully utilize the massive multithreading and highly parallel processing capabilities of our discovery engine.
We know you’ve got to integrate data into our discovery platform from many different sources. And that you likely have to consider offloading processing from other analytic solutions. That’s why our software stack is standards based, adhering to the W3C specifications for RDF and SPARQL used for graph analytic processing.
All of this adds up to a complete package we deliver where all the hardware, software, and management tools for big data discovery are already integrated, tested, and optimized. You get an easy-to-deploy, purpose-built appliance that delivers rapid time to value and a single point of support.
Your analysts can be up and running within hours of your Urika installation…