Databricks is gunning for Snowflake’s core business

In a shot across the bow to Snowflake, Databricks is set to announce on Tuesday that its flagship data warehouse product has achieved record performance levels.

Ali Ghodsi, CEO of Databricks.

Databricks is poised to announce that an independent industry group validated results which show that Databricks' systems outperformed the closest data warehouse competitor by 2.2x.

Photo: Databricks

The rivalry between Databricks and Snowflake is about to become even more hostile. And the outcome could have monumental ramifications for one of the most foundational pieces of modern computing.

Databricks is pushing a new architecture known as the data lakehouse, one that backers say will obliterate the need for data warehouses, the de facto industry standard for decades. Such a move would be akin to a new browser design eliminating Google Chrome. And it's clear why Databricks has Snowflake in its sights: The company commands a market cap of $107 billion after re-architecting the data warehouse for the cloud era.

On Tuesday, that goal will get a big boost. Databricks is poised to announce that an independent industry group known as the Transaction Processing Performance Council (TPC) validated results which show that Databricks' systems outperformed the closest data warehouse competitor by 2.2x.

"We basically proved that we can beat [Snowflake] at their own game, which is the data warehousing game," CEO Ali Ghodsi told Protocol.

It's deeply technical, but at a high level, Databricks SQL — the company's flagship data warehouse product — was able to execute "32,941,245 queries in one hour on a large data warehouse of size 100 TB," according to a blog post scheduled to be released Tuesday morning. On top of the speed accomplishment, Databricks said it achieved this milestone with a 10% cost reduction from the prior record holder, Alibaba.

Snowflake, as well as others in the industry, are bound to try to counter those claims in some capacity — whether publicly or behind the scenes with customers. And the distinction from the TPC is unlikely to have an immediate material impact on Databricks' financials.

"At the enterprise level, maybe some CIO is going to care about what your official TPC ranking is, but they don't make sales that way," said Carnegie Mellon University associate professor Andy Pavlo.

'That's worth paying attention to'

But while the influence of the TPC has waned over the years, it still carries weight.

Started in the 1980s, the organization serves as somewhat of a neutral umpire in the world of evaluating database performance. The TPC publishes benchmarks that companies can run their systems against. The group then reviews the results for official certification.

As the industry has exploded and grown hyper-competitive, those benchmarks may be adding more confusion than clarity. Some vendors, for example, tout results that haven't been officially approved by the TPC.

Databricks said the latest results were "audited and made public" by the TPC. And the size of the increase in performance is noteworthy, enough to perhaps perk the ears of some potential customers.

"That's worth paying attention to," said Pavlo.

Regardless, Databricks still has some way to go to surpass its rival. Less than 10% of its revenue comes from Databricks SQL but the product is growing "very fast," Ghodsi said.

Still, it's the latest in a series of moves and announcements by Databricks intended to amp up the competition with Snowflake to new heights. The company has been putting the $3.5 billion raised from investors to date to hire top talent focused on building out its competing product to Snowflake's.

Michalis Petropoulos joined in June as a senior director of engineering. He previously helped lead Google's BigQuery team and oversaw all of Amazon Redshift. And Sridhar Machiraju, who previously led the Spanner team at Google, joined in November also as a senior director of engineering.

That's just a fraction of the over-a-dozen former AWS, Google, Snowflake and IBM employees that have joined Databricks in the past year. And more hires are looming: Amit Shukla, who was a director of engineering at Google, is slated to join later this month.

"Our team that is working on the core data warehouse ... is probably actually larger than Snowflake's at this point," Databricks co-founder Reynold Xin proclaimed.

Between the recent fundraising rounds, TPC results and slew of new hires, it's clear Databricks has momentum. And with over $600 million in annual recurring revenue as of Aug. 31, it's also clear that there is enthusiasm for the company's data lakehouse model.

But it's a tough road ahead. And while Ghodsi is quick to proclaim the end of the data warehouse is near, it'll take much more than an audit from an industry body to not only kill one of the industry's dominant vendors, but displace a tech that has maintained its popularity in the world of enterprise tech for the past 20 years.


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

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

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.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
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.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.


Why large enterprises struggle to find suitable platforms for MLops

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.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

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.

Latest Stories