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Databricks Raises $60 Million To Be Big Data’s Next Great Leap Forward

15 December, 2016

Databricks Raises $60 Million To Be Big Data’s Next Great Leap Forward

Looking to be the next leap forward in data organization, computation, and delivery for big data Databricks, the business built on top of the popular Apache Spark open source project, has raised $60 million in new financing.

Taking the route mapped by so many big data companies before it, Databricks is the business that the open source Apache Spark project built.

Spark is the next step in data scientists’ long march to make massive amounts of data easy to understand and use in the next generation of applications.

Data processing at velocity and volume has any number of applications in today’s data-rich world. And the victor — the company that can process that data and effectively serve it up in a way that folks inside businesses can understand and use effectively — will take the most spoils.

The Spark project is part of an open source family of tools under the Hadoop umbrella that has already collected a ton (and I mean A TON) of cash.

Companies like Cloudera, which raised roughly $1 billion (actually $900 million — including $760 million from Intel) during the effervescent days of 2014, came to market with claims of a better way to store and manage large amounts of data far more cheaply than any previous infrastructure technology.

It’s the stuff that companies like Facebook and Google use to process the billions of pieces of data that they collect. Spark… is the next step… focusing not on the storage of data, but on how to manage it most effectively. The two work in concert, but are not the same.

With its latest financing, led by the company’s previous investor, New Enterprise Associates, and including participation from Databricks’ initial investor Andreessen Horowitz, the company is looking to take its tech to the next level.

The San Francisco-based company has already taken its product through some pretty intense paces, wresting the pole position in the CloudSort benchmark from an open source offering developed by the University of California, San Diego.

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