Databricks hits $188 billion valuation as enterprise AI spending accelerates

Databricks hits $188B valuation, extending its run as AI's favorite second act

Databricks on Thursday announced a new round of funding that values the company at $188 billion. The round was led by Coatue. Databricks didn't disclose exactly how much it raised; it said the money isn't in its hands yet and that the round will close later in this summer. (Other outlets have since reported the raise is roughly $3 billion.) While it's unusual for a company to announce before it gets the money, a VC tells TechCrunch that the deal is solid, with so many firms wanting in that the company had no reason to keep its shiny new valuation a secret. In fact, Databricks has been on a year-and-a-half fundraising tear as it successfully transitioned its image into an AI provider and not just a yesteryear SaaS sensation. Yesteryear being back in the BC times (Before ChatGPT). Only five months ago, in February, Databricks closed a $5 billion Series L raise at a $134 billion valuation. Five months before that, in September 2025, it raised $1B at $100 billion valuation. And roughly nine months before that, in December 2024, it raised what was a record-breaking round at the time of $10 billion at a $62 billion valuation. Databricks has raised so many rounds over the years that this latest one became the subject of memes about running out of letters of the alphabet. "Turning on alerts for when we get a Series AA," one person posted. But its image reconstruction has been legit. Founded in 2013, it initially grew to success back in the big data era, with software that enabled enterprises to store enormous amounts of data in the cloud, yet produce speedy analytics. Because it already sat on troves of enterprise data, Databricks was then well-positioned to respond as companies started wanting AI with the same security and governance they expect from traditional enterprise software. The company began rolling out one AI product after another, like Lakebase, its database built for AI agents, and Unity, its AI gateway, along with a "meta-harness" called Omnigent that manages multiple agents. Databricks also increasingly became known as one of the big examples of enterprises adopting more affordable Chinese-based open-weight models (models whose underlying code is published for anyone to use and modify) for cost control, one of the big trends of 2026. It is a particular champion of Z.ai's GLM 5.2 as a model for coding. Last week Databricks CEO Ali Ghodsi shared the results of some internal benchmarking done to manage his own AI costs for his 3,000 software engineers. The company compared AI models on the actual tasks its programmers do. Not surprisingly, in the blog post revealing the results, Databricks shared that "open models, and GLM 5.2 in particular, are now able to handle even the highest level of task difficulty" in coding, and at a total lower cost than proprietary models from Anthropic and OpenAI. But it did surprise people by finding that the choice of harness -- the agentic coding tool, like Codex or Claude Code, that wraps around a model and manages its context and instructions -- equally impacted costs. It found that open-source harness, Pi, to be one of the best at managing context surrounding each prompt, and therefore one of the lowest costs choices without sacrificing quality. "The lesson here isn't that one harness is always cheaper or that native harnesses are worse. Instead, model choice is only one piece of the puzzle," the post declared. All of this has added to Databricks image as an AI company, even if it wasn't founded as an AI lab. This, in turn, has granted it the AI-halo for raising money and leaping its valuation. As we previously reported, the AI effect is so strong these days, that even sandwich shop Jersey Mike's mentioned AI 22 times in its S-1 documents.

Databricks hits $188bn valuation in Coatue-led round, landing above its own $175bn talks

The data and AI firm keeps raising, and keeps insisting it is in no rush to go public. $188bn is a large number for a company that keeps insisting it is in no rush to go public. That is the valuation Databricks has reached in a new funding round led by Coatue Management, a figure first reported by the Wall Street Journal. The mark sits well above the up-to-$175bn the firm was reportedly in talks to raise at only weeks earlier, so the round is landing higher than the chatter that trailed it. It also arrives in a market its own chief executive recently dismissed as a terrible year to go public, which makes a private raise the obvious move. Coatue is investing roughly $3bn, according to the Journal, in a strategic round that draws in both new and existing backers. A term sheet has been signed, and the deal is expected to close later this summer, with neither the fund nor the company commenting publicly. Strategic rounds of this shape do two useful things at once. They top up a balance sheet for spending on infrastructure and acquisitions, and they let early staff and backers take some money off the table, all without the disclosure a stock market demands. The valuation caps a giddy climb. Databricks closed a $5bn round at $134bn in February, paired with $2bn of debt, itself a sharp jump from the $62bn it commanded in a $10bn Series J a little over a year before. The interim chatter had pointed at figures between $165bn and $175bn, so $188bn clears even the top of that range. That is close to a trebling of paper value inside 18 months. It lifts Databricks into a tier of private companies whose valuations now shade past plenty of mid-cap listed firms, without any of the quarterly scrutiny that comes with a ticker. A $188bn private mark is less a price than a message, that large investors would rather own the company off the public market than wait for it to arrive on one. Scarcity, in other words, is doing some of the work that revenue used to. The business underneath is substantial. Databricks sells a platform for ingesting, analysing, and building AI applications on tangled corporate data, and competes most directly with the publicly listed Snowflake, whose own market value gives investors a rough yardstick for what a listed Databricks might fetch. It says revenue is running above $5.4bn a year and growing more than 65%, the kind of curve that keeps private investors comfortable paying up. The fresh capital follows a busy stretch that included buying Panther Labs to push into cybersecurity. Ambition has not been in short supply elsewhere. Co-founder Matei Zaharia recently collected an ACM Prize and declared that AGI is here, which is one way to rationalise a valuation climbing faster than most public indices. On the listing question, the company stays deliberately coy. Ali Ghodsi has said Databricks will go public eventually, just not into 2026's crowd, with SpaceX, OpenAI, and Anthropic between them expected to soak up something close to $200bn in IPO capital; the latter two have since filed their paperwork. Databricks has not said what the fresh money is earmarked for, and Reuters noted no use-of-proceeds statement. Its recent pattern, though, is easy to read, with spending flowing toward AI tooling, data infrastructure, and the odd acquisition, the sort of investment that reads better on a private ledger than a quarterly earnings call. Raising privately at this level is not free of consequence. The higher the private mark, the harder the eventual price discovery, and a debut that opened below $188bn would read as a down-round that no amount of ARR could disguise. For now the money is staying private, and the term sheet is signed. The next number that matters is whichever one a prospectus eventually dares to print against $188bn.

Databricks opens strategic funding round at $188bn valuation

Last August, co-founder and CEO Ali Ghodsi told the Wall Street Journal that, in his view, 'Databricks has a shot to be a trillion-dollar company'. US software and data analytics company Databricks is raising a strategic funding round at a $188bn valuation following the signing of a term sheet, it said yesterday (16 July). The round is led by existing investor Coatue and is expected to feature additional new and existing investors before closing later this summer. The San Francisco-based company offers a services platform around data and AI that aims to help build and scale apps, analytics, and agents for more than 20,000 client organisations such as Adidas, AT&T, Bayer, Block, Mastercard and Unilever. Databricks said the new funding would be used to "accelerate its AI strategy" through a focus on three of its core offerings: Unity AI Gateway, a "multi-AI governance solution that helps enterprises govern and control costs of their AI"; Genie, an "AI coworker that turns business data into trusted answers and actions"; and Lakebase, a "serverless 'Postgres' database built for AI agents". "Enterprises are moving from 'tokenmaxxing' to 'valuemaxxing'," said Ali Ghodsi, co-founder and CEO of Databricks. "They don't want to burn expensive tokens on the smartest model for every task - they want the best outcome per dollar. That means having the freedom to choose the right AI for the job. "This new capital lets us keep pushing our multi-AI strategy forward to meet massive customer demand". The funding would also contribute to supporting future AI acquisitions and deepening AI research, the company said. In February, Databricks was valued at around $134bn after raising $5bn. Last December, it raised around $4bn. In recent times, the company has launched or expanded partnerships with Microsoft, Google Cloud, Anthropic, SAP and Palantir. Its five-year deal with Anthropic, valued at $100m, offers Anthropic's Claude AI models through Databricks' data intelligence platform, allowing its more than 15,000 client companies to build and deploy AI agents that can reason on their own data. Last August, Ghodsi told the Wall Street Journal that, in his view, "Databricks has a shot to be a trillion-dollar company". Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.

Databricks Is Now Worth $188 Billion. Its Next Move Could Reshape Enterprise AI

Databricks is raising fresh capital at a $188 billion valuation -- $54 billion more than investors valued the company at five months ago. The round gives co-founder and CEO Ali Ghodsi more money to expand the company's enterprise AI platform while easing the pressure to go public. The San Francisco data and AI company said Thursday that it signed a term sheet for a strategic funding round led by existing investor Coatue. The deal is expected to close later this summer. Databricks did not disclose the size of the round. PitchBook estimates it at $3 billion in preferred-stock financing, with new and existing investors expected to participate.

Databricks Just Hit A $188B Valuation: Co-Founder Ion Stoica On AI Bubble, Jobs, And Why Humans Still Mat

In a quiet conversation just before Databricks signed a $188 billion funding round, co-founder Ion Stoica laid out why enterprise AI is moving from "tokenmaxxing" to "valuemaxxing" and what it means for everything from open source to jobs. But in a quiet conversation just before the news broke, Databricks co-founder Ion Stoica wasn't talking about valuations. He was explaining why the real race is no longer about building the most powerful model. It's about helping companies pick the right one, for the right job, at the right cost. Ion Stoica, a serial entrepreneur and UC Berkeley professor, now splits his time among Databricks, the distributed-computing unicorn Anyscale, and his newest venture, Arena. The latter grew out of a 2023 Berkeley research project that posed a deceptively simple question: when two chatbots answer the same prompt, how do you know which is better? How Arena Became the Referee of the AI Wars The platform is already evolving beyond human feedback. Ion Stoica revealed Arena is building its own models to simulate users and predict preferences, enabling automated evaluation at scale. That same technology powers Max, an intelligent routing product that picks the best model for a given prompt, potentially under cost constraints, and is already available to users. The next frontier is agentic AI. Arena recently launched evaluations for agentic workloads and is enabling agentic modes on its site, tools like OpenManus that are "very popular, going very fast." The Open-Source Gambit Ion Stoica has long been an open-source evangelist. Databricks itself grew out of Apache Spark, the open-source data processing engine he helped create at Berkeley's AMPLab. But his support for open-source AI models comes with a hard-nosed caveat. "Obviously, you want open source, people will not use an open source model just because it's open source, at least in most cases...they have to be very high quality", - he said. "We do have the large open source models which are very high quality, a lot of them coming from China today." That observation lands differently in July 2026 than it would have a year ago. With US export controls tightening on the most powerful American models and China signaling potential export controls of its own, Ion Stoica sees a geopolitical tailwind for open source. "I think we are going to see more and more organizations, enterprises betting on the open source models because they provide the most reliable access to intelligence". He noted how quickly the landscape shifts: "One year and a half ago or two years ago, the best open-source models were from the US: Meta's Llama models and so forth. Things are changing fast." On AI Bubbles, Jobs, and Why Humans Still Matter The Three Rules for Building the Next Unicorn Ion Stoica has started and scaled multiple companies now: from Databricks to Anyscale, to Arena. When asked for advice for today's entrepreneurs, he doesn't talk about prompt engineering or model architecture. He talks about passion, trust, and bets. "Number one, you start a company because you are passionate about the problem that company is going to solve," he said. "You shouldn't start a company just because you want to start a company, you want to own a company, you want to be the CEO of the company." Rule two is about the team. "There are going to be ups and downs. And as humans, when things are going down, you are going to start to point fingers and you are not going to point fingers to yourself. So, that kind of trust is very important to move over these kinds of hardships." After our conversation, I thought about Ion Stoica's three rules for founders. Passion. Trust. A differentiated bet. Databricks' latest round is the market's verdict that the bet is still paying off. The question for the rest of us isn't whether AI will reshape work. It's whether we'll be the ones deciding what problem to solve, or the ones waiting for someone else's model to hand us an answer. Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga's reporting and has not been edited for content or accuracy. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Databricks Hits $188 Billion Valuation, Raises Strategic AI Funding Round

Databricks has secured a strategic funding round at a $188 billion valuation to accelerate enterprise AI innovation, strengthen Unity AI Gateway, Genie, and Lakebase, and expand AI research, acquisitions, and multi-AI infrastructure for global customers. Data and AI company Databricks has announced a new strategic funding round that values the company at $188 billion, underscoring growing investor confidence in enterprise artificial intelligence. The financing is expected to close later this summer and is being led by existing investor Coatue, with participation from additional new and existing investors. The fresh capital will be used to strengthen Databricks' AI portfolio, expand research efforts, and support future acquisitions as the company seeks to meet rising enterprise demand for AI-powered business solutions.

Databricks CEO said they are 'running out of GPUs everywhere' By Investing.com

Investing.com - Databricks' valuation has surged to $54 billion in just five months, reaching $188 billion as the company signed a term sheet on July 16, 2026, for a roughly $3 billion funding round led by existing investor Coatue Management. The catalyst for the latest raise, according to CEO Ali Ghodsi, is blunt: the company is running out of computing power. "We are running out of GPUs," Ghodsi said on CNBC, framing the GPU shortage not as a near-term planning challenge but as an operational constraint pressing hard on the business right now. Surging demand for Databricks' open-source AI model hosting has apparently exhausted GPU capacity across multiple regions, making fresh capital a matter of operational necessity rather than opportunistic growth financing. "Demand has been so strong that we are running out of GPUs across multiple regions," he added. "We nearly exhausted our GPU capacity in Asia, and demand is rising in countries including Japan, South Korea, the United States, and India. We, therefore, need to acquire a large number of additional GPUs, which requires significant funding. That demand was what triggered our latest fundraising round: we were inundated with customer requests and needed more GPU capacity. GPUs are extremely expensive to acquire." Nvidia (NASDAQ: NVDA) is the direct public-market beneficiary of this dynamic. As one of the largest private AI infrastructure platforms urgently adding GPU capacity, Databricks represents exactly the category of enterprise demand that underpins Nvidia's data center revenue trajectory. The $188 billion valuation marks a remarkable ascent even by the standards of the current AI fundraising cycle. Databricks closed a $5 billion Series L round in February 2026 at a $134 billion valuation, meaning the new round -- expected to close later this summer -- adds $54 billion in implied value in roughly five months, according to TechCrunch. That February round itself followed a $1 billion raise at a $100 billion valuation in September 2025 and a $10 billion raise in December 2024. This latest effort would mark the company's fourth major capital raise in approximately 19 months. Ghodsi spelled out where the new money is headed. Beyond GPU procurement, Databricks intends to accelerate a multi-AI strategy spanning Unity AI Gateway, its Genie AI coworker product, and Lakebase, a serverless Postgres database built for AI agents. The company is also signaling appetite for further AI acquisitions. Ghodsi framed the strategic backdrop in terms of enterprise priorities: "Enterprises are moving from tokenmaxxing to valuemaxxing. They don't want to burn expensive tokens on the smartest model for every task, they want the best outcome per dollar. That means having the freedom to choose the right AI for the job," he said. The GPU shortage Ghodsi describes is not unique to Databricks, but the public admission of capacity exhaustion at a company valued at $188 billion illustrates just how severe the structural compute crunch has become across the AI industry. Databricks is hosting open-source models, including Z.ai's GLM 5.2, which it has championed for coding tasks, and that hosting business has scaled faster than its GPU inventory can support. Whether the company plans to buy hardware outright, lease cloud capacity, or negotiate a dedicated supply arrangement with a major chip vendor has not been disclosed. The $3 billion figure itself carries a caveat: it is sourced from the Wall Street Journal's reporting, citing people familiar with the matter, and Databricks has not officially confirmed the dollar amount. Analysts widely regard Databricks as one of the most likely IPO candidates in the near-term pipeline, alongside OpenAI and Anthropic, both of which have already filed IPO paperwork.