adataoDeborah Gage of The Wall Street Journal reports, “Making big data stores as easy to search as Internet data has been a holy grail for the software industry, and it’s become a more pressing problem since the growth of the big data software Hadoop, which holds enormous amounts of data. Adatao Inc., a startup based in Sunnyvale, Calif., has raised nearly $13 million in Series A funding led by Andreessen Horowitz to take on the challenge. Founded in 2012 by veterans of Google Inc., Yahoo Inc. and the Army Research Lab, the company combines machine learning, natural language processing and in-memory (i.e. fast) computing to create a system in which users can write queries in ordinary English or one of several computer languages-—Smart Query, SQL, Scala, Java, Python or R–and get results in less time than it takes to speak their questions.”

Gage goes on, “They don’t need to know the type of data they’re looking for–the system pulls in any data that’s readable by Hadoop. ‘We think of ourselves as the missing puzzle piece that connects Big Data 1.0 over the last five years to the future of Big Data 2.0,’ said co-founder and Chief Executive Christopher Nguyen, a former engineering director of Google Apps. ‘…With Hadoop, there’s so much storage and so very little insight.’ Adatao is among a handful of startups that has bet its future on Apache Spark, an open source project at the University of California, Berkeley’s AMPLab that provides a more solid foundation for Big Data applications by unifying disparate components of Hadoop. Apache Spark is being commercialized by Databricks Inc., another startup that’s backed by Andreessen Horowitz.”

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Image: Courtesy Adatao