Enterprise

When is Databricks going public? 'Six months at a time,' says CEO Ali Ghodsi.

Armed with a fresh $1.6 billion, Databricks is trying to fend off competitors to own the data lakehouse market as it preps for an IPO.

​Databricks CEO Ali Ghodsi speaks during a 2019 Bloomberg Television interview.

Databricks CEO Ali Ghodsi believes Databricks is already well on the path to becoming a public company.

Photo: David Paul Morris/Bloomberg via Getty Images

It's a big question in enterprise tech right now: When will Databricks go public? The answer will have to wait.

The startup just raised another huge round of private capital ahead of its IPO, which could happen this year. The new $1.6 billion Series H round values Databricks at a jaw-dropping $38 billion. New investors include BNY Mellon, ClearBridge and the University of California's investment fund.

Money is no object in Silicon Valley these days, but to put that in perspective: There's only a handful of private startups, including TikTok owner ByteDance, that are valued higher. It's even more wild when considering that the products Databricks sells are deeply technical and targeted towards skilled developers. In other words: This isn't teenagers dancing to snippets of Olivia Rodrigo's album, it's heavy-duty artificial intelligence.

The latest fundraising round won't impact its IPO timeline, per CEO Ali Ghodsi. In fact, he believes Databricks is already well on the path to becoming a public company.

"We're going public six months at a time," Ghodsi told Protocol. "Usually when you IPO, you want to make sure you are getting the long-term investors … [and] we're basically allocating the big blocks of allocations to the big mutual funds and other investors right now," he added.

The investors in question are Franklin Templeton, which participated in February's $1 billion round, and Morgan Stanley, which was involved in the latest one. Another key audience that is likely watching the IPO timeline with great interest? Databricks employees.

When you look at the last few funding rounds, "it's not a lot of dilution, single digit percentages," Ghodsi said. "The company is getting more diluted by the people we hire every year … [and] that dilutes the company more than fundraising."

Databricks has offered "multiple liquidity events for our employees," per Ghodsi.

And a key reason Databricks needs to keep the continual flow of capital is to establish the data lakehouse — an architecture it created that blends together the data warehouse and the data lake — as a permanent category, as well as fend off competition from upstarts and the cloud giants. That means hiring pricey engineers and pouring money into research and development, among other costly undertakings.

"Building a whole data and AI stack, creating a new category, it's going to take a lot of investment," said Ghodsi. "We love the cloud vendors ... but there is also overlap with them. There is Snowflake. If you look at the market, all of those are massive companies with massive balance sheets."

Joe Williams

Joe Williams is a writer-at-large at Protocol. He previously covered enterprise software for Protocol, Bloomberg and Business Insider. Joe can be reached at JoeWilliams@Protocol.com. To share information confidentially, he can also be contacted on a non-work device via Signal (+1-309-265-6120) or JPW53189@protonmail.com.

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Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

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The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

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AWS CEO: The cloud isn’t just about technology

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Photo: Noah Berger/Getty Images for Amazon Web Services

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Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

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Image: Protocol

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As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

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Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

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