Microsoft Corporation Furthers Cloud Push with Metanautix Acquisition | Techno stream

Microsoft Corporation Furthers Cloud Push with Metanautix Acquisition

23 Dec 2015 | Author: | No comments yet »

Microsoft Acquires Big Data Startup Metanautix.

Terms were not disclosed, but Palo Alto, California-based Metanautix had raised about $7 million in venture funding from Sequoia Capital and others since its founding in 2012. Microsoft has acquired a young Palo Alto startup called Metanautix, a firm specializing in helping large enterprises filter through their hordes of in-house data.This is accomplished through private and public clouds -such as traditional data warehouses, business systems like Salesforce, and NoSQL databases like Cassandra- without undergoing the complex and expensive process of bringing all data to a centralized system.

Terms of the deal haven’t been disclosed Cofounded in 2012 by Theo Vassilakis and Toli Lerios, who previously worked at Google and Facebook respectively, Metanautix launched in September 2014 shortly after raising $7 million and after two years in development. Apart from that, Microsoft has been extremely coy about the deal, though the company’s acquisition does fit into CEO Satya Nadella’s plans to build an “intelligent cloud”, one of Redmond’s three main investment areas announced earlier in the year. The company sells its technology to big firms wishing to pool its myriad of data sources from across departments and divisions, covering databases and business systems such as Salesforce, to serve up meaningful insights.

His co-founder is Apostolos Lerios, a former Facebook FB -2.05% senior engineer who worked on that company’s photo service, which is home to billions of our own photos and other images. When the company publicly launched, this publication reported that it had “half a dozen beta customers using [its] software.” Despite that, its run as an independent shop is over. Once it’s it pooled together all the necessary info, businesses can employ SQL to query the subsequent data pipeline so that the users can obtain insights from the information.

Metanautix applied the standard SQL (the initials stand for structure query language) used to ask questions of traditional relational databases to wild-and-wooly data that doesn’t fit into that row-and-column mold. Microsoft intends to fold Metanautix into its “data platform, including SQL Server and the Cortana Analytics Suite.” For now, the software giant is publicly light on details past those notes. This deal is an additional step in Microsoft’s stratagem to provide businesses machine learning, powerful analytics, and artificial intelligence capabilities to enable them to become more prolific in an age of data production.

Vassilakis confirmed further plans on the roadmap. “Metanautix started out with the vision to integrate the data supply chain by building the Quest data compute engine that enables scalable SQL access to any data,” said Vassilakis in a blog post. “Three years in, we can take this work to the next level by joining forces with Microsoft. Being able to apply that same tool to messy non-relational data, in theory means that businesses can learn much more from their diverse data sources in one fell swoop.

It manages to say even less than you might expect, but did find space for its CEO to thank his employees: “It’s been a thrilling ride, but before we begin the next exciting chapter I’d like to take a moment to thank our amazing team who has made all of this possible[.]” With just $7 million raised, and most of that in years past, it isn’t impossible to guess that the company was light on cash at the time of the sale, heading into a far more challenging fundraising climate than when it launched. Microsoft has made almost 20 acquisitions this year, and “cloud” has featured prominently, including cloud security startup Adallom and cybersecurity firm Secure Islands. So a business analyst for a product manufacturer could ask how much of Product A sold in the second quarter, but also parse posts on Twitter or Facebook to see how customers liked or didn’t like what they bought.

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