Microsoft ‘s latest acquisition is a Palo Alto startup called Metanautix, which specializes in filtering hordes of data for big organizations. For now, the terms of the deal have not been disclosed. Metanautix has essentially created a tool dubbed as Quest, which allows SQL queries against any data regardless of where it is.
The startup was founded by a former engineer at Google Theo Vassilakis, where he was heading a similar project called Dremel for finding all kinds of data housed in different locations using SQL queries. After working for Google, he decided to create something of his own that led to the foundation of Metanautix where he created Quest.
The start-up was launched in September last year right after raising $7 million, helping companies sift through the massive data along with covering enterprise systems such as Salesforce to give meaningful insights.
“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 Metanautix’s Vassilakis in a blog post. “Three years in, we can take this work to the next level by joining forces with Microsoft. We look forward to being part of Microsoft’s important efforts with Azure and SQL Server to give enterprise customers a unified view of all of their data across cloud and on-premises systems.”
Going by Microsoft’s recent acquisitions, Metanautix could fit into Redmond giant’s recent quest to build a more “intelligent cloud”. One of three key areas of investment under the leadership of Satya Nadella.
“Companies continue to generate enormous volumes of information and aspire to be more data-driven in their strategies and operations,” said Microsoft VP Joseph Sirosh in a blog post. “But many struggle to bring together their various sources and silos of data, and only analyze and use a fraction of all the available information. Metanautix’ technology breaks these boundaries to connect the ‘data supply chain,’ no matter what the type, size or location of an organization’s data.”
