Updated: December 14, 2025 (14/12/2025)
Databricks has become one of the most closely watched private tech companies in the AI era—not because it builds chatbots, but because it sits underneath them. Its platform is where enterprises store, govern, process, and increasingly activate data for analytics and AI. That position at the center of “AI in production” is now showing up in the numbers investors care about most: valuation multiples, growth, and margin dynamics.
Here’s the cleanest way to understand Databricks valuation today—what’s confirmed, what’s being reported, what secondary markets are signaling on December 14, 2025, and what could determine whether a rumored valuation jump holds up into an eventual IPO window.
Databricks valuation today: what’s confirmed vs what’s reported
Because Databricks is private, its valuation is not a live public-market figure. The “headline valuation” you’ll see depends on which yardstick you use: the last disclosed funding round, a reported in-progress round, or a model-driven “private market price” estimate.
1) Confirmed baseline: Series K at >$100 billion
Databricks publicly announced in August 2025 that it had signed a term sheet for a Series K round that valued the company at more than $100 billion, and described the round as already oversubscribed. [1]
A few weeks later, the company also reported major scale signals as it moved to close that round, including crossing a $4 billion revenue run-rate, surpassing a $1 billion AI product revenue run-rate, and achieving positive free cash flow over the last 12 months. [2]
2) Reported next step: talks around $134 billion
In the most widely cited recent report, Reuters reported on Nov. 30, 2025 that Databricks is in talks to raise $5 billion at a $134 billion valuation, citing reporting from The Information and investor materials—while noting Reuters could not independently verify and that Databricks declined to comment. [3]
That same Reuters report ties the proposed valuation to a very specific framing: roughly 32x expected 2025 sales of about $4.1 billion, alongside commentary that Databricks has increased its sales projections multiple times this year and expects 55% sales growth. [4]
TIME’s AI newsletter echoed the same “raising at $134B” framing in early December, describing Databricks as a quieter but consequential AI infrastructure player. [5]
3) The “today” signal: secondary-market-derived prices (not an official valuation)
On the private secondary side, Forge lists a Databricks “Forge Price” of $197.14 with a Forge Price Date of 12/14/2025, while still showing the post-money valuation figure as $100B (reflecting the last funding baseline rather than the rumored round). [6]
Meanwhile, Nasdaq Private Market says its “Tape D®” estimate had Databricks at $191.93 per share last month, based on market activity and other inputs (and it requires sign-in for deeper real-time detail). [7]
Important context: These price-per-share indicators can be useful sentiment checks, but they are not equivalent to a single, universally agreed “Databricks market cap” the way public stocks work—especially because private share classes, preferences, and transfer restrictions can materially affect implied valuation.
How Databricks got here: a valuation timeline that explains the jump
Databricks’ current valuation conversation makes more sense when you zoom out to the last 12–15 months:
- Dec. 17, 2024: Databricks announced a $10B Series J valuing the company at $62B, describing it as expected “non-dilutive” financing and noting intent to provide liquidity for employees and pay related taxes. [8]
- Aug. 19, 2025: Databricks announced the Series K term sheet valuing it at >$100B. [9]
- Sep. 8, 2025: Databricks disclosed $4B revenue run-rate, $1B AI product revenue run-rate, and positive free cash flow over the last 12 months, as it closed $1B of Series K capital. [10]
- Nov. 18 and Nov. 30, 2025: Reuters reported the company was discussing fundraising at >$130B and later $134B, citing The Information and noting no signed term sheet at that time. [11]
Taken together, the narrative is clear: Databricks’ valuation has been “step-functioning” upward at the same time that enterprise AI spend is shifting from pilots to platforms.
Why investors are paying up: the business signals behind Databricks valuation
A $134B headline is eye-catching. The deeper question is: what is it pricing in?
Growth + scale: revenue run-rate and AI revenue run-rate
Databricks’ own disclosures in September 2025 highlighted a combination that private investors tend to reward with premium multiples:
- $4B revenue run-rate, growing >50% YoY [12]
- $1B AI product revenue run-rate [13]
- Positive free cash flow over the prior 12 months [14]
- Net retention rate >140% (a “land-and-expand” signal) [15]
When a private company can combine growth, retention, and improving cash profile, it tends to unlock higher valuations—especially if investors believe the TAM (total addressable market) expands with AI.
The platform position: Databricks as “enterprise AI plumbing”
Even critics of AI hype tend to differentiate between consumer AI products and the infrastructure required to deploy AI inside large organizations. Databricks’ pitch is not “we have the best model.” It’s “we can safely turn enterprise data into usable AI applications and agents.”
That theme is explicit in Databricks’ own Series K announcement, which described plans to expand Agent Bricks and build out Lakebase (its database push) while investing in global growth and acquisitions. [16]
And it’s consistent with how the CEO framed the company’s trajectory in media coverage through 2025, including investor appetite and the strategic shift toward databases and AI agents as growth vectors. [17]
The key tension inside the $134B story: AI is lifting revenue—and pressuring margins
One of the most important details in the recent valuation reporting isn’t the $134B number. It’s the reason investors might hesitate at that number: the economics of AI workloads.
Reuters reported that Databricks told investors its gross margin is falling faster than anticipated to 74% vs an earlier plan for 77%, attributing the pressure to increasing usage of AI products. [18]
This matters because AI features often turn software into something closer to “software + compute delivery.” In plain English: if customers use more AI, Databricks may have to pay more to serve those workloads—unless it can re-price, optimize, or shift usage to higher-margin structures.
That margin story also connects to a broader market shift: Business Insider recently highlighted an AlixPartners view that AI could make traditional SaaS metrics like ARR less decisive, because consumption-based AI economics can make revenue more volatile and valuation models more hybrid. [19]
Translation for Databricks valuation watchers: If Databricks can keep growth high while stabilizing AI-driven cost of revenue (or charging in a way that preserves gross margin), premium multiples are easier to defend. If margin compression accelerates, private valuations can become harder to sustain at IPO time.
Databricks vs Snowflake: why the comparison keeps showing up in valuation debates
Nearly every Databricks valuation discussion pulls in Snowflake for one reason: it’s the closest public-market benchmark for cloud data platforms at scale.
A recent industry analysis pointed out that, at least using the assumptions in those reports, Databricks’ rumored fundraising valuation implies a higher revenue multiple than Snowflake’s public-market multiple—highlighting how much future growth the private market might be pricing into Databricks. [20]
This “Databricks vs Snowflake” framing also persists because:
- Snowflake’s valuation is set daily by public markets.
- Databricks’ valuation is set episodically by private rounds and secondaries.
- Investors try to triangulate where a Databricks IPO could land by anchoring to public comps, then adjusting for growth, margins, and AI narrative.
What the private market is signaling on 12/14/2025
If you’re trying to reconcile the $100B baseline with $134B reports, the secondary market is the real-time “third lens.”
- Forge lists a Databricks Forge Price of $197.14 dated 12/14/2025 and shows the post-money valuation (from the last funding) as $100B. [21]
- Nasdaq Private Market says its Tape D estimate put Databricks around $191.93 per share last month. [22]
What you can responsibly infer:
- The private-market “price signals” look directionally consistent with a company that has maintained strong investor demand since the $100B round.
- They do not confirm a $134B round is completed (or even signed), because that requires an actual financing close with terms.
IPO forecast: what 2026 could look like for Databricks valuation
No one can give a single definitive “Databricks IPO valuation” today—because it depends as much on the public market multiple environment as on Databricks’ own execution.
Still, three forecast paths are emerging from recent reporting and market dynamics:
Scenario A: The $134B round closes and becomes the new anchor
If Databricks closes new capital anywhere near the reported $134B, that price becomes the natural anchor for IPO expectations—especially if growth remains near the levels implied in recent reporting. [23]
Scenario B: Databricks stays private longer—and uses liquidity programs to reduce IPO pressure
TechCrunch reported that Databricks has already run multiple employee liquidity opportunities, and that employees had chances to sell significant portions of their holdings in 2025 depending on holding size. [24]
This pattern is consistent with a broader private-market reality: companies can delay IPOs by offering periodic tender offers or structured secondaries—especially when they can still raise capital privately at premium valuations.
Scenario C: Public-market multiples reset, forcing valuation discipline
Even if Databricks executes well, IPO valuation is constrained by what public investors will pay for:
- forward revenue growth,
- gross margin durability,
- free cash flow trajectory,
- and AI differentiation that feels sustainable rather than cyclical.
And as the Business Insider/AlixPartners framing suggests, the AI shift may also push investors to demand clearer unit economics around consumption and outcome-based pricing—not just classic subscription expansion. [25]
What to watch next: the catalysts most likely to move Databricks valuation
If you’re tracking Databricks valuation into 2026, these are the practical, valuation-moving questions:
- Does a new round actually close at ~$134B—and with what structure?
A primary-heavy round, a secondary-heavy round, or a hybrid can each signal different priorities (growth capital vs liquidity vs cap table management). - Do AI workloads improve product stickiness without permanently eroding gross margin?
The reported margin dip to 74% is a key datapoint because it shows AI adoption isn’t “free.” [26] - Do Databricks’ newer bets (Agent Bricks, Lakebase) translate into measurable revenue expansion?
Databricks has positioned these products as major growth drivers for its AI strategy and database ambitions. [27] - What happens to secondary market pricing through Q1 2026?
With Forge showing $197.14 as of today, shifts in these derived prices can foreshadow investor sentiment before any IPO filing. [28]
Bottom line: Databricks valuation is becoming a proxy for enterprise AI confidence
As of December 14, 2025, the most accurate way to state “Databricks valuation” is:
- Confirmed: Databricks has publicly anchored itself at >$100B via its Series K announcement and subsequent business performance disclosures. [29]
- Reported: Databricks is in talks for a funding round that could value it around $134B, tied to expected sales and strong growth—but not yet confirmed as closed. [30]
- Market signal today: Secondary-market-derived estimates show Databricks trading around the high-$190s per share range (model-based), supporting the view that demand remains elevated. [31]
The next major inflection point will be whether Databricks can keep its AI-driven growth engine running while proving that the economics (especially gross margin) can scale with it—because in the AI era, valuation is no longer just about “software,” it’s about who can profitably deliver intelligence at enterprise scale.
References
1. www.databricks.com, 2. www.databricks.com, 3. www.reuters.com, 4. www.reuters.com, 5. time.com, 6. forgeglobal.com, 7. www.nasdaqprivatemarket.com, 8. www.databricks.com, 9. www.databricks.com, 10. www.databricks.com, 11. www.reuters.com, 12. www.databricks.com, 13. www.databricks.com, 14. www.databricks.com, 15. www.databricks.com, 16. www.databricks.com, 17. techcrunch.com, 18. www.reuters.com, 19. www.businessinsider.com, 20. blocksandfiles.com, 21. forgeglobal.com, 22. www.nasdaqprivatemarket.com, 23. www.reuters.com, 24. techcrunch.com, 25. www.businessinsider.com, 26. www.reuters.com, 27. www.databricks.com, 28. forgeglobal.com, 29. www.databricks.com, 30. www.reuters.com, 31. forgeglobal.com
