Updated August 2026: Three developments have reshaped the Databricks IPO story since this analysis first published. First, on June 4, 2026, CEO Ali Ghodsi told Bloomberg Television that 2026 is “a terrible year to go public,” explicitly ruling out a 2026 listing and pointing instead to a possible IPO as early as 2027. Second, on June 8–9, 2026, The Information reported that Databricks was in talks for a new private funding round at a $165–$175 billion valuation. Third, that round has since closed: CNBC reported in August 2026 that Databricks wrapped a $5 billion funding round at a $190 billion valuation – a roughly 42% jump from its $134 billion mark just eight months earlier. Fourth, the underlying business kept accelerating right alongside the valuation: CMSWire reported that same month that Databricks’ revenue run rate had surpassed $7 billion, growing more than 80% year-over-year in the second quarter of 2026 – and research firm ValueAdd VC independently clocked the jump from $134 billion to $190 billion as a 42% valuation increase in its own August 2026 tracking. Fifth, Ghodsi doubled down on the eventual listing itself: on August 13, 2026, days after the new round closed, he told TechTarget flatly, “we will go public,” even while continuing to treat 2026 as off the table. In short: Databricks is choosing to stay private and raise more capital rather than file an S-1 this year. The financial profile below remains anchored to the company’s own confirmed figures – a run rate that climbed from $5.4 billion to more than $7 billion between February and August 2026, growth accelerating past 80% year-over-year, a net retention rate above 140%, and positive free cash flow – but the timeline has shifted from “imminent IPO” to “well-capitalized private company on its own schedule.”
Databricks has not filed for an IPO and, as of August 2026, has explicitly signaled it will not go public this year – with CEO Ali Ghodsi pointing to a possible public offering as early as 2027, depending on market conditions, in what could still become the largest enterprise software IPO in history. Databricks’ revenue run rate reached $5.4 billion (up more than 65% YoY as of February 2026) before climbing past $7 billion, growing more than 80% year-over-year in Q2 2026, according to both CNBC and CMSWire’s August 2026 reporting, with over 800 customers spending at least $1 million annually and more than 70 spending at least $10 million annually, positioning it as one of the most compelling private technology companies for a future public offering. Rather than list, the company has instead closed a new $5 billion private funding round at a $190 billion valuation, CNBC reported in August 2026 – up from the $165–$175 billion range reported in talks just weeks earlier.
The stakes are enormous. Databricks had already raised over $7 billion in total funding across equity and debt – a more than $4 billion Series L at its $134 billion valuation that closed in December 2025, per Allied VC’s tracking of the deal, plus a $1.8 billion debt financing led by JPMorgan in January 2026 – before closing a further $5 billion round at a $190 billion valuation in August 2026, per CNBC. CEO Ali Ghodsi told CNBC in December 2025 that he “wouldn’t rule out a 2026 IPO,” but reversed that stance on June 4, 2026, telling Bloomberg Television: “We will be a public company. I just think this is a terrible year to go public.” The company now appears set to remain private – freshly capitalized at a $190 billion valuation – with a listing more likely in 2027.
This is not just another tech IPO story. Databricks sits at the intersection of two of the most powerful trends in enterprise technology: cloud data infrastructure and artificial intelligence. The company’s Lakehouse platform, which unifies data engineering, analytics, and machine learning, has become the backbone of enterprise AI adoption. And with AI products generating a $1.4 billion annual revenue run rate as of February 2026, Databricks is monetizing the AI boom in ways that few other companies can match.
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Why the $134 Billion Valuation Changes the IPO Calculus
Databricks’ $134 billion private valuation, achieved in its Series L round closed in December 2025, made it the most valuable private enterprise software company in the world – and as of August 2026, CNBC reports the company has closed a fresh $5 billion round at a $190 billion valuation, pushing that mark even higher than the $165–$175 billion range reported in talks just weeks earlier. To put that in perspective, rival Snowflake – a publicly traded company – trades at a market capitalization of roughly $78 to $82 billion at approximately $249 per share as of late June 2026. Databricks is now valued at more than double its closest public competitor while still private.
The math behind that valuation tells a compelling story. At a $5.4 billion annualized revenue run rate growing more than 65% year-over-year, Databricks commands a $134 billion private valuation – with a new round pricing it at $165–$175 billion – while Snowflake trades publicly at roughly $80 billion on product revenue of $1.33 billion in its most recent quarter (Q1 fiscal 2027), growing 34% year-over-year. The premium reflects the market’s belief that Databricks’ faster growth rate, AI product traction, and platform breadth justify a significantly higher multiple.
But that premium also creates risk. If Databricks eventually goes public at or near its private valuation – potentially $165–$175 billion or higher after the new round – it would need to sustain exceptional growth to justify the price. Any deceleration – even from 65% to 45% – could trigger a sharp correction. Enterprise software investors have been burned before by companies that went public at peak growth multiples only to see their stocks crater as growth normalized. Ghodsi’s June 2026 decision to stay private a while longer may, in part, be a bet on letting the public-market window improve before testing that valuation.
The Financial Profile: $5.4 Billion in Revenue and Positive Free Cash Flow
Databricks announced on February 9, 2026, that it had crossed a $5.4 billion annualized revenue run rate, marking more than 65% year-over-year growth – a figure market-intelligence outlet Quantlogix said it had already tracked as early as January 2026, with research firm Teahose likewise reporting the $1.4 billion AI products run rate by that same month. Momentum only built from there: CMSWire reported in August 2026 that the run rate had surpassed $7 billion, with year-over-year growth accelerating past 80%. The company also disclosed that AI product revenue had surpassed a $1.4 billion run rate, that its net retention rate exceeded 140%, and that more than 800 customers were consuming at over $1 million annually – with more than 70 customers consuming at over $10 million annually. In head-to-head evaluations Databricks continues to win a large share of incremental AI/ML budget, while Snowflake’s Cortex AI and intelligence products remain comparatively earlier stage.
Perhaps most importantly for future IPO investors, Databricks achieved positive free cash flow over the past year. This is a critical milestone. Public market investors in 2026 are far less tolerant of cash-burning growth stories than they were during the 2020 to 2021 era. Snowflake, by contrast, has continued to operate at a GAAP net loss despite strong revenue, facing ongoing scrutiny over its path to GAAP profitability. Databricks’ ability to generate cash while growing at more than 65% is a powerful differentiator – and one of the reasons it can afford to delay an IPO and raise private capital instead.
The company’s revenue mix is also shifting in a favorable direction. Lakebase, Databricks’ serverless Postgres database optimized for AI agent workloads, now has thousands of customers and is growing revenue at twice the pace of the company’s data warehousing products. This signals that Databricks is not just riding the AI hype cycle – it is building products that enterprises are willing to pay for at scale.
Databricks vs Snowflake: The $134 Billion Rivalry by the Numbers
A Databricks IPO will inevitably invite comparisons to Snowflake, which went public in September 2020 in the largest software IPO in history at the time, raising $3.4 billion at a $33 billion valuation. Snowflake’s stock surged 112% on its first day of trading, briefly reaching a market cap above $70 billion. Today, the comparison between the two companies reveals a dramatically different competitive landscape – one in which Databricks is choosing to stay private at a $165–$175 billion valuation while Snowflake trades publicly around $80 billion.
| Metric | Databricks (Private, 2026) | Snowflake (Public, Q1 FY2027) |
|---|---|---|
| Revenue / ARR | $5.4B annualized run rate | $1.33B product revenue (Q1) |
| Revenue Growth (YoY) | 65%+ | 34% |
| Valuation / Market Cap | $134B (new round in talks at $165–$175B) | ~$78–82B (public) |
| AI Product Revenue | $1.4B+ run rate | Not separately disclosed |
| Enterprise Customers ($1M+) | 800+ | 733 |
| Enterprise Customers ($10M+) | 70+ | Not separately disclosed |
| Free Cash Flow | Positive | Positive (non-GAAP); GAAP net loss |
| Net Revenue Retention | 140%+ | 126% |
| Remaining Performance Obligations | Not disclosed | $9.21B (+38% YoY) |
The numbers paint a clear picture: Databricks is growing nearly twice as fast as Snowflake, generates a substantially larger total revenue base, has achieved positive free cash flow, and reports a higher net retention rate (140%+ versus Snowflake’s 126%). Snowflake’s $9.21 billion in remaining performance obligations (up 38% year-over-year) and 126% net revenue retention rate show that it remains a formidable competitor with strong customer commitment, but the momentum has shifted decisively in Databricks’ favor.
The $7 Billion War Chest: How Databricks Funded Its IPO Runway
Databricks’ funding history reads like a masterclass in strategic capital raises. The company has raised over $7 billion in combined equity and debt, including approximately $5 billion in equity at its $134 billion valuation and roughly $2 billion in debt capacity – and as of June 2026 is in talks to raise yet another private round at a $165–$175 billion valuation. The scale of these raises is staggering for a private company and reflects both the intensity of investor demand and Databricks’ decision to fund growth privately rather than tap the public markets in 2026.
The funding timeline accelerated dramatically from 2024 through 2026. In December 2024, Databricks raised $1 billion in a Series J round that valued the company at $62 billion, per Sacra. By August 2025, Reuters reported the company was eyeing a valuation above $100 billion in a new late-stage round, a 61% jump from that $62 billion prior mark, alongside projected annual revenue of $3.7 billion by that July – roughly 50% year-over-year growth. That round closed the following month: in September 2025, Databricks confirmed a $1 billion Series K at a valuation above $100 billion, oversubscribed by 20 times. Then in December 2025, the company closed its massive $4 billion-plus Series L at the $134 billion valuation. Just weeks later, in January 2026, JPMorgan led a $1.8 billion debt financing. And by August 2026, CNBC and Reuters both reported Databricks had wrapped yet another round – $5 billion at a $190 billion valuation – capping a 20-month run in which its valuation roughly tripled from $62 billion.
Jason Lemkin, a prominent SaaS investor and founder of SaaStr, noted in early 2026 that “unless the market crashes, I think they’re both [Anthropic and Databricks] going to IPO in the back half of ’26.” Ghodsi’s June 2026 comments complicate that view: with SpaceX, OpenAI, and Anthropic preparing to absorb more than $200 billion of IPO capital, Databricks has opted to sit out the crowded 2026 window. The IPO is still a question of when, not if – but “when” now points to 2027.
Ali Ghodsi’s Vision: From Apache Spark to AI Platform
Databricks’ journey from an open-source project to a $134 billion-plus company is inseparable from the vision of CEO Ali Ghodsi. A co-founder of the company and a former UC Berkeley researcher who helped create Apache Spark, Ghodsi has guided Databricks through a series of strategic pivots that have kept it ahead of the market – and, in June 2026, made the contrarian call to stay private through a crowded IPO year.
The most consequential of those pivots was the introduction of the Lakehouse architecture, which unified the traditional data warehouse and data lake into a single platform. This move, which Databricks began championing in 2020, effectively created a new product category that forced competitors – including Snowflake, Google BigQuery, and Microsoft Fabric – to respond with their own unified offerings.
More recently, Ghodsi has positioned Databricks as an AI-native platform. The acquisition of Mosaic ML in 2023 for $1.3 billion gave Databricks the ability to train large language models on enterprise data. The subsequent launch of products like Lakebase, a serverless Postgres database designed specifically for AI agent workloads, and Genie, a conversational AI assistant for data querying, has extended the platform into the fast-growing agentic AI market. The company’s $1.4 billion AI product revenue run rate validates this strategy.
Ghodsi confirmed in February 2025 that the company had its board structure, auditing systems, and financial reporting fully in place for a public listing. “We are IPO-ready,” he said. He reiterated that readiness in June 2026 even as he ruled out a 2026 listing: “We will be a public company. I just think this is a terrible year to go public.” The decision to go public, in other words, remains purely a matter of timing and market conditions – now pointed toward 2027.
The $850 Million UK Expansion and Global Growth Strategy
On March 31, 2026, Databricks announced an $850 million investment in the United Kingdom over three years, including a new 137,000-square-foot London headquarters that quadruples the company’s existing UK office footprint. The investment signals Databricks’ ambition to expand aggressively beyond the United States, a strategy designed to show future public market investors that the company’s growth story is not geographically limited.
The UK expansion is particularly significant because more than 50% of FTSE 100 Index companies are already Databricks customers. The company cited data showing that UK enterprises plan to increase AI investment by an average of 40% over the next two years, creating a favorable environment for Databricks’ growth in the region. The new London office will serve as the company’s EMEA headquarters.
This kind of strategic global expansion is a classic pre-IPO playbook. By demonstrating international traction with blue-chip enterprise customers, Databricks is building the narrative that a $165–$175 billion-plus valuation is supported by a truly global addressable market – not just domestic demand – whenever it does choose to list.
The 2026 IPO Class: How Databricks Stacks Up Against Other Mega-Listings
Databricks would not be going public in isolation. The second half of 2026 is shaping up to be one of the most active IPO windows for technology companies since 2021 – and that crowding is precisely why Databricks is sitting it out. As Ghodsi noted, mega-listings from SpaceX, OpenAI, and Anthropic are expected to absorb more than $200 billion of IPO capital, making 2026, in his words, “a terrible year to go public.”
| Company | Expected Valuation | Sector | Expected Timeline | Revenue (Known) |
|---|---|---|---|---|
| SpaceX | $1.25-1.75 trillion | Aerospace / Telecom | Mid-to-late 2026 | Not disclosed |
| OpenAI | $500-840 billion | AI Models | Late 2026 | Not disclosed |
| Anthropic | $183-380 billion | AI Models | H2 2026 | Not disclosed |
| Databricks | $165–$175B (round in talks) | Cloud / Data / AI | Likely 2027 (delayed) | $5.4B run rate |
| Canva | ~$40 billion | Design Software | 2026 | Not disclosed |
| Strava | ~$2.2 billion | Fitness / Consumer | Spring 2026 | Not disclosed |
What distinguishes Databricks from the AI-native companies on this list is its established enterprise revenue base and positive free cash flow. While OpenAI and Anthropic are expected to go public at higher valuations, their profitability timelines remain uncertain. Databricks offers public market investors something increasingly rare in the AI sector: a company that is both growing at a hyper-growth rate and generating cash – which is exactly why it can afford to wait for 2027 rather than compete for attention in a saturated 2026 calendar.
The AI Product Engine: How $1.4 Billion in AI Revenue Is Reshaping the Business
Databricks’ disclosure that AI product revenue surpassed a $1.4 billion run rate is one of the most significant data points for prospective IPO investors. It demonstrates that the company is not merely adjacent to the AI boom – it is a direct beneficiary. AI revenue now represents roughly a quarter of Databricks’ total run rate, and it is growing at a rate that suggests it could become the majority of revenue within two to three years.
The AI product suite includes several key offerings. Mosaic ML, acquired for $1.3 billion in 2023, enables enterprises to train custom large language models on their own data. Databricks Model Serving, which lets customers query foundation models directly inside the platform, added support for Anthropic’s Claude Sonnet 5 in June 2026, according to Databricks’ own release notes – keeping the platform current with the latest frontier models. Lakebase provides serverless Postgres database infrastructure optimized for the read-heavy, low-latency workloads that AI agents require. Genie offers a conversational AI assistant that allows non-technical users to query enterprise data using natural language. And Unity Catalog provides the governance layer that enterprises need to manage data access and compliance across AI workloads.
The rapid growth of Lakebase is particularly noteworthy. Launched in mid-2025, the product has attracted thousands of customers and is growing revenue at twice the pace of Databricks’ core data warehousing business. This kind of product-led growth within an existing enterprise customer base is exactly what public market investors want to see – it suggests that Databricks can expand wallet share even as its customer count grows, as evidenced by a net retention rate above 140%.
Risks and Red Flags for IPO Investors
Despite the bullish narrative, there are material risks that prospective IPO investors need to weigh carefully. The most obvious is valuation risk. At $134 billion – and potentially $165–$175 billion after the new round – Databricks is priced for perfection. Any miss on growth, margin, or guidance when it eventually lists could result in a punishing sell-off, particularly if the broader market environment deteriorates.
There are also competitive risks. The cloud hyperscalers – Amazon Web Services, Google Cloud Platform, and Microsoft Azure – all offer competing data and AI platforms. AWS has Redshift and SageMaker. Google has BigQuery and Vertex AI. Microsoft has Fabric and Azure AI. These companies can bundle their data platforms with compute, storage, and other cloud services in ways that Databricks cannot, creating pricing pressure and switching cost advantages.
Timing risk is now part of the calculus too. By delaying its IPO to 2027, Databricks is betting that public-market conditions will be more favorable then than during the crowded 2026 window. But that bet carries its own exposure: if enterprise software multiples compress further, or if a successful 2026 listing by a rival resets the comparable set unfavorably, the delay could prove costly. Leadership stability is another concern, as Databricks has navigated senior departures while preparing for the public markets.
Finally, there is the macro environment. Enterprise software stocks have been volatile throughout 2025 and into 2026. As one market observer noted, “plummeting software stocks aren’t good news for any company with a big enterprise business that is considering going public.” Ghodsi’s June 2026 decision to stay private and raise a fresh round, rather than list into a turbulent and crowded market, is a direct response to exactly that risk.
The JPMorgan Factor: What the $1.8 Billion Debt Raise Signals
The $1.8 billion debt financing that Databricks secured in January 2026, led by JPMorgan, was widely read as a signal that an IPO was approaching. Pre-IPO debt raises of this magnitude serve multiple purposes: they provide working capital for continued investment without further equity dilution, they establish a banking relationship with a potential IPO lead underwriter, and they demonstrate to the market that major financial institutions are willing to underwrite Databricks’ creditworthiness. With the IPO now pushed to 2027, that war chest also buys the company the flexibility to wait.
JPMorgan’s involvement is particularly telling. The bank has led some of the largest technology IPOs in recent years and typically does not underwrite debt for private companies unless it has visibility into an eventual public offering. The debt raise, combined with the $4 billion-plus Series L equity round from just weeks earlier, gave Databricks total combined capital of more than $7 billion – a war chest that provides maximum flexibility in choosing the optimal IPO window, even if that window now sits in 2027.
The structure of the debt financing – roughly $2 billion in total debt capacity – also suggests that Databricks is planning for significant capital deployment. Combined with the new $165–$175 billion equity round in talks as of June 2026, this could fund strategic acquisitions, geographic expansion beyond the $850 million UK investment, or accelerated hiring to support the company’s AI product roadmap. With more than 9,000 employees already, Databricks is operating at a scale that rivals mid-cap public technology companies.
Market Conditions: Is the IPO Window Open or Closing?
The timing of Databricks’ IPO depends heavily on market conditions – and as of June 2026, the company has decided the window is too crowded to enter this year. The enterprise software sector has experienced significant volatility in 2025 and early 2026, with investors rotating between AI optimism and growth skepticism. Ghodsi’s assessment that 2026 is “a terrible year to go public” reflects a judgment that a 2027 listing is more likely to command full value.
First, the broader AI infrastructure buildout continues to drive enterprise spending. Companies across every sector are investing heavily in data platforms and AI capabilities, creating a favorable demand environment for Databricks’ core products. The $850 million UK investment and the 40% increase in AI spending planned by UK enterprises are microcosms of a global trend.
Second, Databricks’ financial profile is well-suited to the current investor mindset. Positive free cash flow, 65%-plus revenue growth, a net retention rate above 140%, and diversified revenue streams across data engineering, analytics, and AI products give the company a balanced story that appeals to both growth and value investors. Unlike many AI companies that are pre-revenue or burning cash, Databricks can point to real, scaled economics – and can therefore afford to fund itself privately while waiting for a better IPO window.
Third, the competitive IPO calendar is the deciding factor. With SpaceX, OpenAI, and Anthropic collectively expected to absorb more than $200 billion of IPO capital in 2026, Databricks has concluded that listing alongside them would mean competing for scarce investor attention. By waiting until 2027, it could establish itself as a benchmark enterprise AI IPO in a less crowded field, potentially commanding a premium.
Five Predictions for the Databricks IPO
1. The S-1 filing will slip into 2027. With Ghodsi explicitly ruling out a 2026 listing in June 2026 and a new private round at $165–$175 billion in talks, the most likely timeline now places the S-1 filing in 2027, after the crowded 2026 mega-IPO calendar clears.
2. The IPO will target a market capitalization above the latest private round. If the new round closes at $165–$175 billion, Databricks will likely seek a premium to that mark at IPO, positioning the offering to generate a first-day pop that rewards early IPO investors without leaving too much money on the table.
3. JPMorgan will lead the underwriting syndicate. The $1.8 billion debt relationship positions JPMorgan as the most likely lead bookrunner, with Goldman Sachs and Morgan Stanley expected to participate as co-leads. The offering could raise $5 to $10 billion, making it one of the largest tech IPOs of the decade.
4. AI revenue will be the dominant narrative in the roadshow. Databricks will position itself as an AI-native platform, not a traditional data company. Expect the S-1 to feature AI revenue, Lakebase growth metrics, and enterprise AI adoption data prominently in the business description sections.
5. Snowflake’s stock will face pressure. A successful Databricks IPO at a $165–$175 billion or higher valuation would create an immediate comparison problem for Snowflake, which trades around $80 billion despite a sizable revenue base. Investors may rotate from Snowflake into Databricks, putting downward pressure on Snowflake shares.
What the Databricks IPO Means for the Broader Cloud and AI Market
The Databricks IPO will be a defining event for the cloud and AI infrastructure market whenever it arrives. A successful listing at $165–$175 billion or above would validate the thesis that enterprise data platforms are among the most valuable businesses in technology. It would also set a benchmark for how public markets value AI-integrated enterprise software – a question that will have ripple effects across the sector.
For Snowflake, the competitive implications are immediate and significant. In its most recent quarter (Q1 fiscal 2027, reported May 2026), Snowflake posted $1.33 billion in product revenue with 34% growth, a 126% net revenue retention rate, 733 customers spending more than $1 million annually, and $9.21 billion in remaining performance obligations. These are strong numbers by any measure. But with Databricks growing faster, reporting higher net retention (140%+), and commanding a valuation premium of roughly 2x, Snowflake may need to accelerate its own AI product strategy to maintain investor confidence.
For the cloud hyperscalers, a public Databricks represents both a competitive threat and a partner opportunity. Databricks runs on AWS, Azure, and Google Cloud, generating significant revenue for all three platforms. But it also competes directly with each hyperscaler’s native data and AI services. The tension between partnership and competition will only intensify as Databricks gains the financial resources and public visibility that come with being a publicly traded company.
The Open Source Advantage: Apache Spark and the Developer Moat
One of Databricks’ most underappreciated competitive advantages is its roots in open-source software. The company was founded by the creators of Apache Spark, the most widely used open-source engine for large-scale data processing. Spark’s ubiquity in enterprise data engineering – used by thousands of organizations worldwide – gives Databricks a built-in distribution channel and developer community that competitors cannot easily replicate.
Databricks has continued to invest in open source as a strategic asset. Delta Lake, the company’s open-source storage layer, has become a de facto standard for lakehouse architectures. MLflow, its open-source platform for machine learning lifecycle management, is one of the most popular tools in the ML engineering ecosystem. These projects create a flywheel: developers adopt the open-source tools, become familiar with the Databricks ecosystem, and then advocate for the commercial platform within their organizations.
This developer-led go-to-market strategy is increasingly important in enterprise software. Companies like HashiCorp, MongoDB, and Elastic have demonstrated that open-source projects can serve as powerful lead generation engines for commercial products. Databricks’ open-source portfolio is arguably the strongest in the enterprise data space, giving it a structural advantage that will be difficult for competitors to erode.
Employee and Talent Implications of Going Public
With more than 9,000 employees, Databricks is already operating at the scale of a mid-cap public technology company. Going public will have significant implications for talent acquisition and retention – and the decision to delay to 2027 has implications of its own. A new $165–$175 billion private round can provide secondary liquidity for early employees in the interim, but it postpones the broader liquidity event that an IPO creates for thousands of vested shareholders.
The $850 million UK investment is partly a talent play. Databricks is competing for AI and data engineering talent against well-funded companies like OpenAI, Anthropic, Google DeepMind, and the cloud hyperscalers. A London EMEA headquarters allows the company to tap into Europe’s deep bench of engineering talent without competing solely in the hyper-competitive San Francisco Bay Area labor market.
Retaining top AI talent remains a challenge in a market where leading researchers and executives can command compensation packages worth tens of millions of dollars. A public listing would give Databricks another tool in its retention arsenal: liquid public equity that can be granted on a rolling basis, reducing the “golden handcuffs” problem that plagues late-stage private companies. Until then, the new private round and existing secondary programs are the bridge.
Data Warehousing Crosses $1 Billion: The October 2025 Inflection Point
One of the most overlooked milestones in Databricks’ pre-IPO narrative is the breakout of its data warehousing product line. By the end of 2025, the company’s data warehousing product surpassed a $1 billion revenue run-rate, contributing to an overall revenue acceleration toward the $4.8 billion run rate amid 55%+ year-over-year growth disclosed in its December 2025 Series L announcement. That single product crossing the $1 billion threshold places Databricks’ warehousing business on the same scale as several standalone, publicly traded data companies.
The significance is competitive. Databricks built its reputation on data engineering and machine learning workloads, while Snowflake dominated the cloud data warehouse category. The milestone proved Databricks could compete head-to-head in Snowflake’s home territory at scale – and that the Databricks SQL warehouse had transitioned from a complementary feature into a standalone billion-dollar business inside the broader Lakehouse platform.
The product’s growth was also a leading indicator for the revenue acceleration that followed. Between the December 2025 disclosure of a $4.8 billion run rate at 55%+ growth and the February 2026 disclosure of a $5.4 billion run rate at 65%-plus growth, Databricks added roughly $600 million in annualized revenue and accelerated its growth rate by ten percentage points in approximately two months – an unusually steep curve for a company at this scale.
The February 9, 2026 Disclosure: $7 Billion in Investments and the IPO Signal
On February 9, 2026, Databricks formally disclosed that it had crossed a $5.4 billion revenue run rate with over 65% year-over-year growth, alongside the completion of more than $7 billion in investments. That total breaks down into approximately $5 billion of equity raised at the $134 billion valuation and $2 billion in debt capacity. The same release confirmed a net retention rate above 140%, more than 800 customers at over $1 million in annual run-rate, and more than 70 customers at over $10 million. The combined disclosure was unusual for a private company, and bankers interpreted it as a deliberate pre-S-1 marketing move.
The timing also closed the loop on a sequence of capital events that began with the December 2025 Series L equity round and accelerated with the January 2026 $1.8 billion debt financing led by JPMorgan. Together, these moves brought total debt and investments above $7 billion. At the time, the size of the JPMorgan facility signaled that Databricks was actively preparing for the public markets – though by June 2026 the company had chosen to extend its private runway with a fresh $165–$175 billion round rather than file.
The 65% growth figure deserves particular attention. Most enterprise software companies decelerate as they scale past $5 billion in revenue, with growth rates typically falling into the 25% to 40% range. Databricks accelerating from 55% to 65% growth at the $5 billion ARR mark is a rare profile – one that, if sustained through an eventual IPO, would justify a meaningful premium over the broader software multiple.
April 2026 Status Check: Where Databricks Stands Pre-IPO
As of June 2026, Databricks has not filed its S-1 publicly, and the company has now explicitly signaled it will not go public this year – a status that held through August 19, 2026, when Allied VC’s tracking of late-stage private companies confirmed no S-1 had been filed and noted that the early-2026 IPO targets had by then been pushed to 2027 or later. That delay hasn’t dampened Ghodsi’s public commitment to eventually listing: on August 13, 2026, he told TechTarget “we will go public,” even as the timeline keeps slipping. That is a notable shift from the mood just weeks earlier: as of June 2026, market intelligence platform Teahose reported that analysts were still expecting a possible filing in the second half of 2026, with valuation chatter clustering near $175 billion. The combination of the February 2026 financial disclosure, the January 2026 debt facility, the December 2025 Series L close, the March 2026 announcement of the $850 million UK investment, and the June 2026 reports of a new $165–$175 billion funding round forms a pattern consistent with a company that is IPO-ready but choosing to stay private through a crowded 2026 listing calendar.
The current state of play, summarized:
- Revenue run rate: $5.4 billion as of February 9, 2026, growing 65%+ YoY
- Net retention rate: Above 140%
- Large customers: 800+ at over $1M annual run-rate; 70+ at over $10M
- Capital raised: Over $7 billion total, including ~$5 billion equity at $134B and $2 billion debt capacity
- New round: In talks at a $165–$175 billion valuation (The Information, June 2026)
- S-1 filing status: Not yet filed; CEO ruled out a 2026 IPO on June 4, 2026
- Likely IPO timing: 2027, per Ghodsi’s comments
The remaining variables are macroeconomic rather than operational. Enterprise software multiples, broader IPO market sentiment, and the timing of competing mega-listings from SpaceX, OpenAI, and Anthropic shaped Ghodsi’s decision to wait. But the company itself appears to have completed the work – financial reporting, governance, capital structure, international footprint – required to go public on its own timetable, which now points to 2027.
May 2026 Update: Company-Confirmed Figures and Current IPO Status
As of June 2026, the picture for Databricks is defined by what the company itself has confirmed – and by the CEO’s own words on IPO timing. Databricks has not filed a public S-1 with the SEC, and on June 4, 2026, CEO Ali Ghodsi told Bloomberg Television that 2026 is “a terrible year to go public,” ruling out a listing this year and pointing to a possible IPO as early as 2027. Days later, on June 8–9, 2026, The Information reported the company is in talks for a new round at a $165–$175 billion valuation.
The most recent company-issued financial figures come from Databricks’ own announcement dated February 9, 2026. In that release, Databricks confirmed it had surpassed a $5.4 billion revenue run rate, growing more than 65% year over year, with a $1.4 billion AI products run rate, a net retention rate above 140%, and positive free cash flow over the trailing 12 months. The earlier December 16, 2025 Series L release confirmed a $134 billion valuation on a $4.8 billion run rate at 55%+ growth. These are the figures investors and reporters can cite directly back to the company.
Those disclosures also surfaced product-level milestones that deserve to stand on their own. Databricks confirmed it had reached more than $1 billion in revenue run rate in its AI products business (now $1.4 billion) and more than $1 billion in revenue run rate in its Data Warehousing business. Two distinct product lines clearing the $1 billion run-rate threshold inside the same company is rare at this stage of growth, and it reinforces the argument that the Lakehouse strategy has matured into multiple billion-dollar businesses rather than a single dominant product.
| Company-Confirmed Metric | Value | Source / Date |
|---|---|---|
| Latest closed valuation | $134 billion | Databricks newsroom, Dec 16, 2025 |
| New round in talks | $165–$175 billion | The Information, Jun 8–9, 2026 |
| Revenue run rate | > $5.4 billion | Databricks newsroom, Feb 9, 2026 |
| Year-over-year growth | > 65% | Databricks newsroom, Feb 9, 2026 |
| AI products run rate | > $1.4 billion | Databricks newsroom, Feb 9, 2026 |
| Net retention rate | > 140% | Databricks newsroom, Feb 9, 2026 |
| Customers at $1M+ / $10M+ | 800+ / 70+ | Databricks newsroom, Feb 9, 2026 |
| Free cash flow (trailing 12 months) | Positive | Databricks newsroom, Feb 9, 2026 |
| Public S-1 filing status | Not filed | As of Jun 2026 |
| 2026 IPO | Ruled out; possible 2027 | Ghodsi, Bloomberg TV, Jun 4, 2026 |
The practical takeaway for June 2026 readers is to separate company-confirmed facts from market timing. The $5.4 billion revenue run rate at 65%+ growth, the $1.4 billion AI run rate, the 140%+ net retention, the positive free cash flow, and the $134 billion closed valuation are all directly attributable to Databricks. The $165–$175 billion figure is a round in talks (per The Information), and the 2027 IPO timing is the CEO’s own stated expectation – both remain subject to change until a deal closes or an S-1 appears in SEC records.
Inside the Series L Syndicate: Who Led the $4 Billion Round at $134 Billion
One detail from the December 16, 2025 Series L announcement deserves a closer look as the June 2026 funding picture firms up: the identity of the investors who anchored the round. Databricks confirmed that the more than $4 billion Series L at a $134 billion valuation was led by Insight Partners, Fidelity Management & Research Company, and J.P. Morgan Asset Management. That lead investor mix is unusual and consequential – and it tells you more about Databricks’ near-term posture than any analyst projection.
The presence of Fidelity Management & Research Company as a lead is the clearest tell. Fidelity is a public-markets crossover investor whose late-stage participations have historically clustered around companies within twelve to eighteen months of a public listing. When a name like Fidelity anchors a Series L at this scale, it is typically positioning to extend that exposure into the IPO and the post-IPO public float. J.P. Morgan Asset Management adds a second crossover signal, separate from but reinforcing the January 2026 $1.8 billion debt facility led by JPMorgan – the bank’s asset-management and banking arms now both have material commercial exposure to Databricks. Insight Partners, a software-focused growth investor, rounds out the syndicate with deep enterprise SaaS underwriting experience at the multi-billion-dollar revenue stage.
That syndicate composition is the kind of detail prospective IPO investors should track. A round led primarily by traditional venture firms would suggest Databricks could comfortably remain private for several more years. A round led by Fidelity and J.P. Morgan Asset Management alongside Insight, by contrast, is a configuration that historically precedes – rather than substitutes for – a public listing, even if that listing now slips to 2027.
Q3 2025 vs February 2026: Reconciling the Two Run-Rate Disclosures
Two different revenue run-rate figures circulate in coverage of Databricks, and as of June 2026 it is worth separating them cleanly. The first, anchored in the company’s December 16, 2025 newsroom release, states that Databricks crossed a $4.8 billion revenue run rate, growing more than 55% year over year, and remained free-cash-flow positive over the trailing 12 months. The second – a $5.4 billion run rate at 65%+ growth – comes from the company’s own February 9, 2026 disclosure and is now the current, company-confirmed figure. Both are directly attributable to Databricks; the February number supersedes the December one.
The defensible profile for a June 2026 reader is therefore: $5.4B run rate, 65%+ growth, $1.4B AI run rate, net retention above 140%, positive trailing-12-month free cash flow, $134B closed valuation (with a $165–$175B round in talks), $4B+ Series L – all sourced to dated company announcements and reputable reporting. The exact IPO timing, target listing valuation, choice of exchange, and bookrunner syndicate remain projection until an S-1 actually appears, with Ghodsi himself now pointing to 2027.
Lakebase at Six Months: A New AI-Native Revenue Engine
The Lakebase product line deserves its own June 2026 read because it is the cleanest example of Databricks compounding existing customer relationships into AI-era revenue. Lakebase, Databricks’ serverless Postgres database built for the age of AI, already has thousands of customers, with revenue growing at twice the pace of the Data Warehousing business – which itself crossed a $1 billion run rate. A young product growing at twice the rate of a billion-dollar product line, inside the same company, is the kind of compounding curve that single-product startups almost never achieve. In its February 2026 update, Databricks named Lakebase and Genie as the two products it is doubling down on.
For prospective IPO investors, the implication is direct. Lakebase converts Databricks’ installed Lakehouse base into a serverless database business optimized for AI agent workloads – meaning incremental AI spend at existing customers can be captured without a separate sales motion, a dynamic reflected in the company’s net retention rate above 140%. If that compounding rate holds, Lakebase could become a third $1 billion-plus product line alongside AI products and Data Warehousing well before any S-1 lockup expires, materially changing the revenue-mix narrative the company brings to the public markets in 2027.
Frequently Asked Questions
When will Databricks go public?
Databricks has not filed its S-1 registration statement with the SEC as of June 2026, and CEO Ali Ghodsi ruled out a 2026 IPO on June 4, 2026, telling Bloomberg Television that 2026 is “a terrible year to go public.” He pointed to a possible listing as early as 2027. The company says it is “IPO-ready” with all necessary board, auditing, and reporting structures in place, but is choosing to remain private and is reportedly raising a new round in the meantime.
What is Databricks’ current valuation?
Databricks was last valued at $134 billion in its Series L funding round, which closed in December 2025 and raised more than $4 billion in equity. As of June 2026, The Information reported the company is in talks for a new funding round at a $165–$175 billion valuation. Including a $1.8 billion debt financing led by JPMorgan in January 2026, the company has raised over $7 billion in combined equity and debt.
How much revenue does Databricks generate?
As of February 2026, Databricks reported a $5.4 billion annualized revenue run rate, growing more than 65% year-over-year. AI product revenue surpassed a $1.4 billion run rate, the net retention rate exceeded 140%, and more than 800 customers were spending over $1 million annually (70+ over $10 million). The company has also achieved positive free cash flow over the trailing 12 months.
How does Databricks compare to Snowflake?
Databricks outpaces Snowflake on growth (65%+ versus 34% in Snowflake’s most recent quarter), net revenue retention (140%+ versus 126%), and valuation ($134 billion private, with a new round in talks at $165–$175 billion, versus Snowflake’s ~$78–82 billion market cap at roughly $249 per share as of late June 2026). Snowflake reported $1.33 billion in Q1 fiscal 2027 product revenue, 733 customers spending more than $1 million annually, and $9.21 billion in remaining performance obligations – still a formidable competitor.
What stock exchange will Databricks list on?
Databricks is expected to list on the Nasdaq stock exchange when it eventually goes public – likely in 2027, per CEO Ali Ghodsi’s June 2026 comments. JPMorgan, which led the $1.8 billion pre-IPO debt financing, is widely expected to serve as lead bookrunner for the offering.
What are the biggest risks of the Databricks IPO?
The primary risks include valuation risk at $134 billion (or $165–$175 billion after the new round), competition from cloud hyperscalers like AWS, Azure, and Google Cloud, leadership changes at a company preparing for the public markets, and broader market volatility in the enterprise software sector. Timing risk is now material too: by delaying its IPO to 2027, Databricks is betting public-market conditions will improve. If growth decelerates or market conditions deteriorate, the stock could face significant selling pressure post-IPO.
What does Databricks itself confirm as of June 2026?
Per Databricks’ newsroom announcement dated February 9, 2026 – the most recent company-confirmed financial disclosure as of June 2026 – Databricks surpassed a $5.4 billion revenue run rate growing more than 65% year over year, with a $1.4 billion AI products run rate, a net retention rate above 140%, more than 800 customers at over $1 million (70+ over $10 million), and positive free cash flow over the trailing 12 months. The December 16, 2025 release confirmed a $134 billion valuation. CEO Ali Ghodsi ruled out a 2026 IPO on June 4, 2026, and The Information reported a new $165–$175 billion round in talks – both of which sit alongside, not in place of, the company-confirmed financials.
Who led Databricks’ Series L round?
Per Databricks’ December 16, 2025 announcement, the more than $4 billion Series L round at a $134 billion valuation was led by Insight Partners, Fidelity Management & Research Company, and J.P. Morgan Asset Management. The mix of a software-focused growth investor (Insight) and two large crossover investors (Fidelity, J.P. Morgan Asset Management) is consistent with positioning for a public listing – now expected to come in 2027.
