Enterprise

Dremio raises $160M Series E for its data lake platform

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Triangular modern lake house in a misty forest at fall.
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Data lake platform Dremio today announced that it has raised a $160 million Series E funding round led by Adams Street Partners. Existing investors Sapphire Ventures (which also led the company’s $135 million Series D round last year), Insight Partners, Lightspeed Venture Partners, Norwest Venture Partners and Cisco Investments also participated in this round.

The company says this preemptive round now brings Dremio’s valuation to $2 billion, up from $1 billion when it raised its Series D round just over a year ago.

“We live in what’s called the SQL lakehouse world,” explained Dremio CEO Billy Bosworth, who joined the company almost exactly two years ago, after eight years as DataStax’s CEO. “What we do is provide technology that allows end-users to access their data in their data lakes directly via SQL — and they can do this in a way that delivers mission-critical BI. What that means is [we’re] giving you the performance that you need to run things like mission-critical dashboards that have sub-second response time capabilities. You can have thousands of analysts hitting the same data sets at the same time with no performance penalty, we call that high concurrency throughput. This is the area that Dremio has been focused on for some time now. We’re going to continue to take that position to the future with a lot of exciting new growth and capabilities in the coming year.”

Dremio — as well as competitors like Databricks — is playing in a newly invigorated market. While data lakes and data warehouses, for the longest time, looked like they would remain useful for a set of relatively limited use cases, the idea of the lake house — which was first popularized by Databricks — is meant to signal that this new class of technologies now allows enterprises to do far more with this data.

“The technology has advanced so much that we felt like there was a need to sort of shift people’s thinking in what those capabilities could be,” Bosworth said. “So by using the term lake house, really, it’s just a connotation that says, ‘oh, so what you’re suggesting is that things that I could do previously only in my data warehouse, are now made possible on data lakes.’”

Unlike Databricks, Dremio’s focus is squarely on SQL workloads, business analysts and mission-critical business intelligence. There is some overlap there with the competition, but Dremio’s mission is quite a bit more focused right now.

“A top priority for every business leader today is to become a data-driven company,” said Brian Dudley, partner at Adams Street Partners. “But data teams are being asked to do the impossible: provide faster time to insights, make all data consumers more self-sufficient, ensure data governance and security, and promote an open architecture to avoid vendor lock-in, all while reducing infrastructure complexity and costs. We believe Dremio is leading the way to empower companies to become data-driven, and we couldn’t be more excited to partner with Billy and the Dremio team on its mission!”

This new funding, of course, gives Dremio a lot of room to aggressively pursue this mission. In addition to expanding its engineering team, the plan is to triple the company’s sales capacity and Bosworth specifically noted that the team plans to greatly expand its go-to-market in Europe this year. But he also noted that having raised this much capital, the company now has the runway to weather any potential headwinds in the global markets for quite some time.

“I think everybody who studies this even for five minutes understands that there are some questions ahead in terms of inflation and what that’s going to do to tech valuations,” he noted. “Nobody knows the answer. The best economists I listened to seem to be all over the map, but the good news is, for us, with this kind of balance sheet, we can execute independently of whatever inflationary winds might hit the markets in the coming years.”

9 investors discuss hurdles, opportunities and the impact of cloud vendors in enterprise data lakes

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