EMC is introducing a new big data appliance that is capable of processing both structured and unstructured workloads, truly taking advantage of some of Greenplum’s latest developments.
The EMC Greenplum Data Computing Appliance, abbreviated DCA, integrates several different technologies to deliver the functionality that the storage vendor is touting. The solution includes Greenplum’s MPP database technology, the HD Hadoop distribution, and analytics and data warehousing tools from certified partners.
“Neither IT departments nor Data Scientists like the idea of maintaining two separate data management platforms – one for structured dat and another for unstructured data – to support analytics projects,” says Wikibon analyst and Big Data specialist Jeff Kelly. “The trend among Big Data platform vendors is to bring the SQL and NoSQL/Hadoop worlds together in a single platform, reducing the management burden on IT departments and allowing Data Scientists to perform all their analysis in a single, unified environment. Today’s announcement from Greenplum is in keeping with this trend.”
EMC says that DCA is 70 percent faster than older data processing technology, and delivers double performance for concurrent query workloads. The appliance supports Data Domain deduplication storage systems, which means that customers willing to pay a premium can get their hands on speedier backup.
EMC is following the lead of several Big Data startups that have successfully taken the mix-n-match route to produce a superior production. One example is Hadapt, with a Hadoop tool that offers extensive support for SQL. The company’s chief data scientist demonstrated this functionality on #theCube back at Strata + Hadoop World back in October — see the full clip here.
Sqrrl is doing something similar – its analytics security offering is based on Accumulo, a BigTable-inspired system that supports both unstructured and structured data. We got the company’s CEO to personally walk us through the nuts and bolts during an interview last year, which you can view here.