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Metanautix Quest Can Be an Organisation’s In-house Compute Engine, much like Google’s Dremel Query System

byadmin
September 10, 2014
in News
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Metanautix, a Big Data analytics startup, made available its flagship product almost two years in the making, called Quest.

Metanautix Quest is a data compute engine that allows the user to navigate through their growing data ecosystem, irrespective of scale or location and getting value out of it through meaningful insight. And its fast.

Ali Hortacsu, Professor of Economics at The University of Chicago, along with HP, Shutterfly and others,  were early customer working closely with the Metanautix team, and spoke of the new offering yesterday,

“Quest is allowing us to analyze hundreds of millions of records in the electricity markets, hundreds of times faster than our traditional data pipeline. Quest has seamlessly integrated into our process, used our existing SQL, and sped our queries dramatically,” he said.

Quest makes it possible for analysts to access and collate “data from disparate silos” in the form of tables — whether its data is records, logs, documents, audio files, images or videos. It is made to work within the existing infrastructure and toolset of the user organisation, discarding any need for a centralised data pool. Existing products in the market that are slightly similar are Cloudera’s Impala and MapR’s Drill, but while these tools have more to do with collection of data, Quest focuses on restructuring the data to make sense of it.

“The concept of a data compute engine is an important paradigm shift,” writes co-founder and CEO, Theo Vassilakis in a statement on the Metanautix website. “Instead of structuring analysis around storage as has been done traditionally, we help you structure analysis around computation – i.e., answering your business question.  A data compute engine is unlike a database engine in that it works with your data wherever it is, be it in a database, a file system, or another application,” he explained.

Read more here

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(Image Credit: Marcin Wichary)

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