Google Cloud to buy file storage specialist Elastifile for $200m

11 July 2019 | Alan Burkitt-Gray

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Google Cloud is to buy enterprise file storage company Elastifile for a reported $200 million.

The giant described Elastifile as a pioneer in solving the challenges associated with file storage for enterprise-grade applications running at scale in the cloud.

Thomas Kurian (pictured), a former Oracle executive who became CEO of Google Cloud only at the start of this year, said that Elastifile has “built a unique software-defined approach to managed Network Attached Storage (NAS), enabling organizations to scale performance or capacity without cumbersome overhead. Building on this technology, our teams are excited to join together and integrate Elastifile with Google Cloud Filestore.”

Erwan Ménard, CEO of Elastifile, said: “File storage is essential to enterprise cloud adoption and, together with Google, we are well positioned to serve those needs.” French-born Ménard has formerly worked in the telecoms industry for Alcatel-Lucent and Hewlett-Packard, and joined Elastifile just over a year ago after being president and COO of Scality.

Ménard says of Elastifile in his LinkedIn entry: “We augment public cloud capabilities and facilitate cloud consumption, by delivering enterprise-grade, scalable file storage within Google Cloud, AWS, and Azure. In December 2018 we launched the Elastifile Cloud File Service, a fully managed service on Google Cloud, offering the best bundles of performance, cost, and features in the industry.”

Until this week’s acquisition, Elastifile, founded in 2013, was backed by LightSpeed Venture Partners and Battery Ventures. Its cloud offering has attracted seven strategic investors, including Dell Technologies Capital, Cisco and Western Digital.

Kurian said: “We believe this combination [of Google Cloud and Elastifile] will empower businesses to build industry-specific, high performance applications that need petabyte-scale file storage more quickly and easily. This is critical for industries like media and entertainment, where collaborative artists need shared file storage and the ability to burst compute for image rendering; and life sciences, where genomics processing and ML training need speed and consistency; and manufacturing, where jobs like semiconductor design verification can be accelerated by parallelizing the simulation models.”