Databricks Valuation: $62B Series J Funding

Last Updated: January 15, 2025. Reflects Databricks' December 2024 Series J funding round.

Valuation figures, ARR data, and investor information are sourced from publicly available reports, company press releases, and financial data providers including Crunchbase and PitchBook. All financial figures should be verified against primary sources before use in professional or investment contexts.

Databricks, the San Francisco-based data and AI platform company, carries a current private market valuation of $62 billion as of December 2024. That figure was established when the company closed its Series J funding round, raising approximately $10 billion from investors including Andreessen Horowitz and Thrive Capital in one of the largest private fundraises in enterprise software history. The $62 billion figure is a post-money valuation (the company's implied worth immediately after a funding round closes), negotiated between Databricks and its investors, not a continuously quoted market price. This article covers Databricks' complete funding history from its 2013 founding through the Series J, the investor roster behind each round, implied ARR multiples at every stage, how the valuation compares to Snowflake, and what the available signals suggest about a potential IPO.

Latest Databricks Valuation Snapshot

• Current valuation: $62 billion
• As of: December 2024
• Round: Series J
• Capital raised (Series J): ~$10 billion
• Total funding raised (all rounds): ~$14 billion+

What Is Databricks' Current Valuation?

Databricks' current valuation is $62 billion, established in December 2024 at the close of the company's Series J funding round. This is a post-money valuation — the implied company value immediately after a funding round closes, calculated by adding the capital raised to the pre-money valuation agreed upon by Databricks and its investors. The $62 billion figure is a negotiated private market price, not a continuously updated stock price, and it will remain the reference valuation until a subsequent funding round or a public listing establishes a new price.

The Series J raised approximately $10 billion, with Andreessen Horowitz and Thrive Capital among the lead investors. Databricks is privately held; its shares are not available for purchase on any public stock exchange as of December 2024.

The valuation figure carries important revenue context. Databricks reported approximately $2.4 billion in Annual Recurring Revenue (ARR) by late 2024, according to reporting by Bloomberg. At that ARR level, the $62 billion valuation implies roughly a 25x ARR multiple. This represents a near-doubling from the $31 billion valuation set at the Series I round in September 2023, driven largely by the generative AI buildout that repositioned Databricks as a core enterprise AI infrastructure company.

What Is Databricks? Company Overview

Databricks is an enterprise software company founded in 2013 by seven researchers from UC Berkeley's AMPLab to commercialize Apache Spark, the open-source distributed data processing engine that co-founder and CTO Matei Zaharia created during his PhD research at Berkeley. Ali Ghodsi, one of the seven co-founders, has served as Databricks' CEO since 2016 and is the company's primary spokesperson on strategy, valuation, and IPO discussions.

The company's core product is a Unified Data Intelligence Platform built on the Data Lakehouse architecture, a design that combines the low-cost, flexible storage of a data lake with the structured query performance and governance of a traditional data warehouse. Databricks coined and popularized the term "Data Lakehouse" around 2020, giving it first-mover positioning in a category it effectively defined. The commercial significance of this architecture is material to its valuation: by serving data engineering, analytics, and machine learning workloads on a single platform, Databricks increases per-customer revenue potential (expansion ARR) and creates a platform lock-in effect that reduces churn. Delta Lake, an open-source storage layer developed by Databricks, provides ACID transaction support and data versioning on top of cloud object storage, and has been adopted by thousands of enterprise customers as a foundational component of the Data Lakehouse. MLflow, an open-source machine learning lifecycle management platform Databricks created in 2018, has become an industry standard for tracking ML experiments, further embedding Databricks' tooling across enterprise data science teams.

Databricks generates revenue through a cloud-based consumption and subscription model. Enterprise customers pay based on usage of compute resources, measured in Databricks Units (DBUs), for data processing, analytics, and ML workloads across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. This multi-cloud, cloud-agnostic positioning differentiates Databricks from competitors like Snowflake, which is more tightly coupled to specific cloud environments.

ARR milestones illustrate the company's growth trajectory: approximately $800 million in 2021, crossing $1 billion in 2023, approximately $1.6 billion in early 2024, and an estimated $2.4 billion by late 2024, according to Crunchbase and Bloomberg reporting. Databricks employed approximately 6,000 people as of 2024. In June 2023, the company acquired MosaicML for approximately $1.3 billion — its largest acquisition to that date — a move that proved decisive for the subsequent Series J valuation. Fuller context on that transaction appears in the funding history section below.

Databricks Key Metrics

• Founded: 2013
• Headquarters: San Francisco, California
• Valuation: ~$62 billion (December 2024)
• ARR: ~$2.4 billion (late 2024, estimated)
• YoY ARR growth: ~50 percent
• Employees: ~6,000+
• Total funding raised: ~$14 billion+
• Public company: No

See the Databricks company overview for official company information.

How Private Company Valuations Work

Private companies like Databricks are valued during funding rounds through a negotiation between the company and its investors, not through continuous public market trading, which is how the share price of a public company like Snowflake is determined.

A funding round is a structured event where a company sells equity to investors in exchange for capital. Each round carries a letter designation — Seed, Series A, Series B, and so on — that reflects the company's maturity stage. A Seed round typically funds early product development; Series A through C rounds fuel initial commercial growth; later-stage rounds (Series D through J and beyond) fund market expansion, acquisitions, and scale-building toward a potential public offering. Databricks' Series J is the tenth documented round in its history, a stage that indicates a company operating at substantial revenue scale with an IPO within a plausible planning horizon.

The valuation at each round is negotiated, not market-determined. Investors and the company agree on a pre-money valuation (what the company is worth before the new capital arrives) and then add the capital raised to arrive at the post-money valuation. If Databricks raised $10 billion at a $52 billion pre-money valuation, the resulting post-money valuation is $62 billion. The primary inputs to that negotiation include the company's ARR, growth rate, market size, and comparable public company valuations; Snowflake's price-to-sales ratio is a standard reference for Databricks rounds.

Between funding rounds, the post-money valuation remains fixed at the agreed figure. Secondary market transactions, where existing shareholders sell equity to new buyers, can provide interim price signals, but those transactions are illiquid and not publicly disclosed. Post-money valuations are not acquisition prices or IPO prices; they are negotiated data points that may not reflect what a strategic buyer would pay or what public market investors would assign at listing.

Why would a company worth $62 billion stay private? Remaining private preserves strategic optionality, avoids the quarterly earnings pressure of public market governance, allows employees to retain equity upside, and delays the pricing complexity of sustaining a $62 billion valuation in a public market. Databricks' management has consistently cited market conditions as the primary variable governing IPO timing.

With this context, Databricks' funding history tells the story of a company that has consistently commanded premium prices relative to its revenue across eleven years of growth.

Databricks Funding Rounds: Complete History

Databricks has completed at least ten documented funding rounds since its founding in 2013, raising a total of approximately $14 billion in cumulative venture and growth capital according to Crunchbase funding data. The valuation trajectory ran from tens of millions of dollars at Seed stage through the unicorn threshold in 2019, the decacorn threshold in 2020, a SaaS bull market peak in August 2021, a deliberate pause through 2022's market correction, and a two-round recovery through 2023 and 2024 driven by the generative AI investment cycle.

The table below traces Databricks' complete funding history from 2013 through December 2024, including estimated ARR at the time of each round and the implied ARR multiple. This combination of columns is not available in any single competing resource.

ARR figures are estimates based on publicly reported data from Databricks press releases, Bloomberg, and PitchBook. All figures should be verified against primary sources before professional use.

The implied ARR multiple column tells a story of investor sentiment: from the growth enthusiasm of the 2021 SaaS peak (~47x ARR) to the AI-driven re-expansion of 2024 (~25x ARR), a normalization that still places Databricks at a meaningful premium to the broader enterprise software sector.

Total Databricks Funding Raised (2013–2024): approximately $14 billion+

Early Rounds: Seed Through Series C (2013–2017)

Databricks' first four rounds funded the commercialization of Apache Spark and the build-out of initial enterprise product capabilities. The company raised approximately $14 million in its 2013 Seed round, backed by Andreessen Horowitz, and used that capital to develop managed cloud infrastructure around Spark, which Matei Zaharia had originally created at UC Berkeley. The relationship between Databricks and Apache Spark is analogous to Red Hat and Linux: open-source credibility combined with commercial enterprise value. By Series C in 2017, the company had reached approximately $1 billion in valuation and was establishing its first major enterprise customer relationships.

Growth Phase: Series D Through Series H (2019–2021)

Series D in February 2019 valued Databricks at approximately $2.75 billion, with Andreessen Horowitz leading a $250 million raise. That round pushed Databricks past the unicorn threshold (a private company valuation above $1 billion in venture capital terminology), though the company had already technically exceeded that mark. By October 2019, the Series E pushed the valuation to $6.2 billion. The Series F in early 2020, at the same $6.2 billion valuation, brought in BlackRock and introduced institutional crossover capital to the cap table.

The Series G in February 2021 reflected the peak of the SaaS bull market. Databricks raised $1 billion at a $28 billion valuation, with an implied ~47x ARR multiple on approximately $600 million in ARR, as institutional appetite for high-growth cloud software reached its zenith. That round pushed Databricks into decacorn territory (a private company valued above $10 billion), placing it among a small cohort of the world's most valuable venture-backed startups. Six months later, the Series H in August 2021 raised $1.6 billion at a $38 billion valuation, sustaining the ~47x ARR multiple on approximately $800 million in ARR. The Series H set a valuation that would not be exceeded until the Series J three years later.

The AI Era: Series I and Series J (2023–2024)

Databricks did not raise a public funding round in 2022, a year in which SaaS valuations broadly compressed 50 to 70 percent as rising interest rates eroded the multiple-expansion that had driven the 2021 peak. The absence of a 2022 raise suggests management deliberately timed the market, preserving the $38 billion Series H valuation as the reference point rather than raising at a compressed multiple.

The Series I, closed in September 2023 and led by Andreessen Horowitz, valued Databricks at $31 billion on $500 million raised. That placed the implied ARR multiple at approximately 19x on roughly $1.6 billion in ARR. The recovery was partly driven by the generative AI investment narrative that emerged following ChatGPT's November 2022 launch. Databricks had already positioned itself for that narrative three months before the Series I closed.

In June 2023, Databricks acquired MosaicML for approximately $1.3 billion. MosaicML was an AI startup founded in 2021 that specialized in efficient training and fine-tuning of large language models (LLMs). The acquisition gave Databricks the capability to offer enterprise customers the ability to train and deploy custom LLMs on their proprietary data within the Databricks platform, competing directly with OpenAI's enterprise offerings and Microsoft's Azure OpenAI Service. MosaicML's technology was integrated into Databricks' product suite and contributed to the March 2024 release of DBRX, Databricks' open-source LLM.

The MosaicML acquisition was the single most important contributor to the Series J valuation narrative, based on the AI platform repositioning it enabled. By December 2024, when Databricks raised approximately $10 billion in its Series J from Andreessen Horowitz, Thrive Capital, and others, the company had shifted its investor narrative from a data infrastructure business to a leading enterprise generative AI platform. The $62 billion Series J valuation represented a doubling of the Series I figure in approximately 15 months.

On approximately $2.4 billion in ARR, the implied ~25x ARR multiple reflected the AI growth premium investors were willing to assign to a company positioned at the center of enterprise AI infrastructure buildout. The size of the round ($10 billion) also signals a capital position consistent with near-term IPO preparation. Other Databricks acquisitions include Redash (data visualization, 2020) and 8080 Labs (notebook tooling, 2021), both of which expanded product capabilities without material valuation impact.

Key Investors in Databricks

Databricks has attracted backing from a diverse mix of venture capital firms, strategic corporate investors, and institutional crossover investors across its funding history, with Andreessen Horowitz (a16z) serving as the most consistent lead investor across multiple rounds.

The table below presents the primary investors in Databricks, their investor type, the rounds they participated in, and a brief note on the strategic rationale for each.

Andreessen Horowitz (a16z) has served as lead investor in multiple Databricks rounds including the Series E and Series G, making it the most influential financial backer in shaping the company's growth capital strategy across six years of rounds.

The presence of strategic investors signals that Databricks' valuation is validated by the largest enterprise technology players. Microsoft, whose Azure platform serves as one of Databricks' primary cloud deployment environments, participated as a strategic investor; Google's GV and CapitalG are aligned with the Google Cloud partnership; and NVIDIA, whose GPU infrastructure powers the AI workloads Databricks customers run on the platform, joined in later-stage rounds. These are the same companies whose platforms Databricks runs on and, in some cases, competes with.

The participation of institutional crossover investors — asset managers who take pre-IPO positions in anticipation of a public listing — is widely interpreted as a signal of near-term IPO readiness. Franklin Templeton joined as early as the Series G in 2021, and T. Rowe Price participated in later rounds. These firms typically build private positions ahead of anticipated public listings to gain exposure before retail investors can participate.

Databricks Valuation vs. Revenue: Implied ARR Multiples

Databricks' $62 billion Series J valuation implies an ARR multiple of approximately 25x, based on the company's estimated $2.4 billion in Annual Recurring Revenue (ARR) — the normalized annualized value of subscription-based revenue, the standard growth metric for SaaS and cloud software businesses — as of late 2024. This section presents the full ARR trajectory and the implied multiple at each major funding round, an analytical layer not available in any single competing resource.

Databricks' ARR Growth Trajectory

Databricks has grown its ARR from approximately $100 million in 2019 to an estimated $2.4 billion by late 2024, a roughly 24-fold increase in five years that underpins the premium valuations investors have assigned at each successive funding round.

All ARR figures are estimates based on Databricks press releases and Bloomberg/Reuters reporting. Databricks does not disclose GAAP revenue as a private company; ARR is the primary metric cited in public coverage.

ARR should not be conflated with GAAP revenue. ARR is the annualized value of active subscription contracts and is the primary metric investors use to benchmark SaaS company valuations. Crossing $1 billion in ARR in 2023 marked a milestone that typically signals enterprise software maturity and IPO candidate status. Databricks' approximately 50 percent year-over-year growth rate at the $2.4 billion ARR level in late 2024 is the primary justification investors cite for the premium implied multiple at the Series J.

Implied ARR Multiples Across Funding Rounds

A revenue multiple (or ARR multiple for private SaaS companies) measures how much investors are willing to pay per dollar of recurring revenue. A company with $2 billion in ARR valued at $50 billion trades at a 25x ARR multiple. The table below applies this calculation to Databricks' major funding rounds from Series D through Series J.

The multiple column traces a clear arc. Multiples expanded from ~28x at Series D to ~47x at the Series G and H peak, then compressed to ~19x at the Series I as the post-2022 SaaS correction reset investor expectations, before partially re-expanding to ~25x at the Series J as the AI growth premium drove renewed enthusiasm.

The compression from ~47x ARR at the Series H peak to ~25x ARR at the Series J reflects both the broader SaaS multiple contraction of 2022 and the AI-driven expansion of 2023 and 2024. The figures suggest investors now value Databricks at a premium to pure-play data warehousing peers but below the speculative heights of the 2021 bull market.

For comparison, Snowflake (NYSE: SNOW) traded at a price-to-sales ratio in the range of 10x to 15x on its GAAP revenue during 2024. The methodological caveat matters here: Databricks' 25x multiple is calculated on ARR (subscription contracts), while Snowflake's price-to-sales ratio is calculated on GAAP revenue recognized over a period. ARR and GAAP revenue can diverge materially depending on contract timing and recognition. Adjusting for this difference, the two companies trade at broadly comparable multiples on an underlying revenue basis, consistent with their similar growth trajectories in enterprise data infrastructure, despite different product compositions.

Databricks vs. Snowflake: Valuation and Competitive Comparison

Databricks' private market valuation of $62 billion, set in December 2024, exceeds Snowflake's public market capitalization as of late 2024 (Snowflake's NYSE: SNOW market cap was approximately $50 billion as of December 2024; verify current price before citing, as this figure changes daily). The comparison requires a methodological caveat: Databricks' $62 billion is a negotiated private round figure set at a single point in time, while Snowflake's market cap is determined continuously by public stock market trading. These figures are not directly comparable, and any analysis treating them as equivalent understates the fundamental difference between private negotiated valuation and public market pricing.

Public company market data as of December 2024. These figures change daily. Verify against current NYSE data before citing in professional contexts.

Snowflake (NYSE: SNOW) completed one of the largest software IPOs in history in September 2020, valued at approximately $33 billion at listing, and peaked above $100 billion in market capitalization in November 2021 before the SaaS correction. Snowflake's product focus is SQL-centric cloud data warehousing and analytics. Databricks covers a broader platform: data engineering, data warehousing (via Delta Lake), machine learning and AI, and LLM training and deployment via the MosaicML acquisition. That platform breadth is a valuation differentiator for Databricks, as wider product coverage means higher expansion ARR per customer and a larger total addressable market. It also introduces more competitive surface area and go-to-market complexity.

At $62 billion, Databricks ranks among the top five most valuable venture-backed private technology companies globally as of 2024, alongside companies such as SpaceX, ByteDance, and Stripe.

Databricks' competitive landscape extends beyond Snowflake. Primary competitors include Google BigQuery (cloud analytics), Amazon Redshift and Amazon EMR (AWS data services), Microsoft Fabric and Azure Synapse (Microsoft's unified analytics platform), and Palantir Technologies (enterprise AI and data). In the AI/LLM development tools space, competition includes AWS SageMaker, Azure Machine Learning, and Google Vertex AI. Analysts frequently debate whether Databricks' AI positioning, bolstered by the MosaicML acquisition, justifies a valuation premium relative to Snowflake, or whether the two companies are converging on similar product surfaces that will intensify pricing pressure over time.

Databricks IPO: What to Expect

As of December 2024, Databricks has not filed an S-1 registration statement with the SEC and has not announced a specific timeline for going public. The company remains privately held, with its shares unavailable for purchase on any public stock exchange.

An initial public offering (IPO) is the process by which a private company lists its shares on a stock exchange for the first time, enabling public investors to buy and sell equity. Databricks has not initiated this process as of the publication date of this article.

Statements in this section regarding Databricks' potential IPO timeline are based on publicly available analyst commentary and market signals, not official company guidance. Actual outcomes may differ materially from any expectations cited below.

The table below summarizes the key IPO prerequisite signals and Databricks' current status against each:

Databricks did not complete an IPO in 2024. Instead, the company raised approximately $10 billion in its December 2024 Series J private round, effectively building further scale before a public listing. This decision is consistent with CEO Ali Ghodsi's stated preference, expressed in multiple press interviews, to pursue an IPO only when market conditions can support the company's private valuation.

Pricing complexity is a genuine constraint. Snowflake's IPO at $33 billion in September 2020 provides one relevant precedent. A Databricks IPO at or above the $62 billion private valuation would represent one of the largest software IPOs in market history and would require public market investors to sustain that valuation under quarterly earnings scrutiny, including scrutiny of the path to profitability. Databricks has historically reinvested heavily in sales, marketing, and R&D, and has not publicly disclosed whether it is profitable on a GAAP basis.

Based on the available signals — ARR scale above $2 billion, institutional crossover investor participation, the capital position established by the Series J, and CEO public statements — analysts broadly anticipate a Databricks IPO within the 2025–2026 timeframe, contingent on market conditions and management discretion. This is analyst expectation, not company guidance. When Databricks does go public, it will likely rank among the largest software IPOs in market history.

Databricks shares are not available for purchase on public markets as of December 2024. Accredited investors may explore pre-IPO equity through secondary market platforms such as Forge Global, EquityZen, or Carta Exchange, though these transactions carry significant liquidity constraints and complexity. Retail investors can monitor for an official IPO announcement, at which point shares would be available through standard brokerage accounts. This is informational content, not financial or investment advice. Investing in private company equity carries significant risk including potential total loss of capital. Consult a qualified financial advisor before making investment decisions.

What Databricks' Valuation Means for Enterprise Customers

For enterprise technology leaders evaluating Databricks as a long-term platform vendor, the company's valuation history tells a story beyond headline numbers. It reflects financial health, investor confidence, and strategic positioning that directly affects vendor stability.

The financial health signals are substantive. Databricks has raised over $14 billion in total capital across eleven years of funding rounds. It reports approximately $2.4 billion in ARR with approximately 50 percent year-over-year growth, a growth rate that implies strong net revenue retention (NRR — a measure of how much existing customers expand their spending year over year). The company serves over 10,000 enterprise customers, a breadth of adoption that reduces the platform-specific concentration risk that affects smaller vendors.

A Databricks IPO, when it occurs, will shift the company from private to public governance, introducing quarterly earnings pressure and public market scrutiny. For enterprise customers, this typically means more financial transparency (S-1 disclosures, quarterly earnings reports) but may also introduce pricing pressure or strategic pivots driven by public shareholder expectations. The transition is not inherently negative, but it changes the governance dynamics that currently allow Databricks to prioritize long-term product investment over short-term margin.

At a $62 billion valuation, Databricks is too large to be acquired by most potential strategic acquirers at current market prices, reducing the acquisition-driven platform disruption risk that affects smaller vendors, though not eliminating it entirely. Microsoft, Google, and Salesforce are among the few companies with balance sheets that could theoretically complete such an acquisition; all three are also strategic investors or cloud partners with interests that complicate any acquisition scenario.

Databricks' continued investment in open-source projects (Apache Spark, Delta Lake, MLflow) signals long-term platform commitment. The company's business model depends on enterprise customers expanding usage, not switching platforms. The MosaicML acquisition and the DBRX LLM initiative reinforce this: Databricks is betting its future valuation on becoming the default enterprise AI infrastructure layer, which means deepening its platform investments, not narrowing them.

If your organization relies on Databricks as a core data platform, the company's $62 billion valuation and $14 billion in capital raised provide reasonable confidence in its ability to invest in product development and infrastructure for the foreseeable future.

Frequently Asked Questions About Databricks Valuation

What is Databricks' current valuation?

Databricks' current valuation is $62 billion, established in December 2024 at the close of its Series J funding round. This is a post-money valuation (the company's implied worth immediately after the round closed), agreed upon between Databricks and its investors. It is a negotiated private market figure, not a continuously updated stock price, and will remain the reference valuation until a subsequent round or public listing establishes a new price. The figure is sourced from Bloomberg's coverage of the December 2024 Series J announcement.

How much funding has Databricks raised in total?

Databricks has raised approximately $14 billion in total funding across at least ten documented rounds from its 2013 Seed raise through its December 2024 Series J, according to Crunchbase data. The largest single raise was the Series J ($10 billion), followed by the Series H ($1.6 billion in August 2021). Earlier rounds ranged from approximately $14 million at Seed to $500 million at Series I.

Who are the major investors in Databricks?

Databricks' major investors include:

• Andreessen Horowitz (a16z): lead investor in Seed, Series A, D, E, H, I, and J; most consistent lead investor
• Thrive Capital: co-lead on Series J
• Sequoia Capital: growth-phase participant
• Coatue Management: growth-stage investor
• GV and CapitalG (Alphabet): strategic investors aligned with Google Cloud partnership
• Microsoft: strategic investor aligned with Azure cloud partnership
• NVIDIA: strategic investor whose GPU infrastructure powers Databricks AI workloads
• Franklin Templeton: institutional crossover investor; pre-IPO positioning
• T. Rowe Price: institutional crossover investor; pre-IPO positioning
• New Enterprise Associates (NEA): early-stage lead investor (Series B and C)

Is Databricks publicly traded?

No, Databricks is not publicly traded. The company is privately held and its shares are not listed on any stock exchange as of December 2024. Databricks remains private following its Series J funding round. The company has been widely cited as a future IPO candidate but has not announced a public listing timeline or filed an S-1 registration statement with the SEC.

How does Databricks' valuation compare to Snowflake?

Databricks' most recent private market valuation of $62 billion (December 2024) exceeds Snowflake's public market capitalization as of late 2024 (approximately $50 billion as of December 2024; verify current NYSE: SNOW price before citing, as this changes daily). The figures are not directly comparable: Databricks' valuation is a negotiated figure set at a single point in time, while Snowflake's market cap is determined continuously by public stock market trading. On an ARR multiple basis, both companies trade at broadly comparable implied multiples when their different revenue bases are accounted for, with the difference partly explained by Databricks' faster growth rate and AI platform positioning.

What does Databricks do?

Databricks is an enterprise software company that provides a unified platform for data engineering, analytics, machine learning, and artificial intelligence. Built on the Data Lakehouse architecture, which combines the scale of cloud data lakes with the structure and governance of traditional data warehouses, Databricks enables organizations to process and analyze large volumes of data and build AI applications on a single platform. Its technology is rooted in Apache Spark, the open-source data processing engine created by co-founder and CTO Matei Zaharia at UC Berkeley.

What is Databricks' revenue?

Databricks does not publicly disclose GAAP revenue as a private company. Based on reported figures, Databricks reached approximately $1.6 billion in Annual Recurring Revenue (ARR) in early 2024, growing to an estimated $2.4 billion ARR by late 2024, according to Bloomberg. This represents approximately 50 percent year-over-year ARR growth. ARR (the annualized value of active subscription contracts) is the primary revenue metric for SaaS companies and differs from GAAP revenue, which is recognized over time rather than annualized at a point in time.

Has Databricks acquired any companies?

Databricks' most significant acquisition was MosaicML in June 2023 for approximately $1.3 billion, an AI startup specializing in efficient training and deployment of large language models that directly repositioned Databricks as a generative AI infrastructure company. The MosaicML acquisition contributed to the valuation doubling from $31 billion (Series I, September 2023) to $62 billion (Series J, December 2024). Other acquisitions include Redash (data visualization tooling, 2020) and 8080 Labs (notebook tooling, 2021). The MosaicML deal is the most strategically significant in terms of its impact on Databricks' investor narrative and subsequent valuation trajectory.

When was Databricks founded, and who are its founders?

Databricks was founded in 2013 by seven researchers from UC Berkeley's AMPLab: Ali Ghodsi (CEO), Matei Zaharia (CTO and creator of Apache Spark), Andy Konwinski, Reynold Xin, Patrick Wendell, Ion Stoica, and Arsalan Tavakoli-Shirazi. The company was created to commercialize Apache Spark, the open-source big data processing framework that Zaharia had developed during his PhD research at Berkeley. The unusually large seven-person founding team, all with academic research credentials, gave Databricks technical depth from its first day of operation.

Is Databricks profitable?

Databricks has not publicly disclosed whether it is profitable on a GAAP basis. As a high-growth private company, Databricks has historically reinvested heavily in sales, marketing, and R&D to sustain rapid revenue growth, a common pattern for enterprise software companies at this stage. CEO Ali Ghodsi has indicated in press interviews that the company is focused on growth rather than near-term profitability, though the company has discussed a path toward profitability as part of IPO preparation. Investors and analysts generally evaluate Databricks on ARR growth rate and net revenue retention rather than current profitability.

Will Databricks do an IPO?

Databricks has not announced an IPO, but analysts broadly anticipate a potential public listing within the 2025–2026 window. Several signals support this expectation: ARR exceeding $2 billion (a standard threshold for enterprise software IPO candidates); CEO Ali Ghodsi's repeated public statements that the company will consider an IPO when market conditions can support its private valuation; the participation of institutional crossover investors (Franklin Templeton, T. Rowe Price) in later-stage rounds, which typically signals pre-IPO positioning; and the size of the Series J raise ($10 billion), which builds a capital position consistent with near-term IPO preparation. All IPO timelines here represent analyst expectations and market signals, not company guidance. Databricks could remain private longer if market conditions are unfavorable.

How can I invest in Databricks?

Databricks shares are not available for purchase on public markets as of December 2024. The company is privately held. Accredited investors may explore pre-IPO equity through secondary market platforms such as Forge Global, EquityZen, or Carta Exchange, though these transactions are illiquid and complex, with eligibility restrictions that exclude most retail investors. Some venture capital funds or ETFs focused on AI and data infrastructure may hold Databricks equity as part of broader portfolios. Retail investors can monitor for an official IPO announcement, at which point shares would be available through any standard brokerage account. This content is for informational purposes only and does not constitute financial or investment advice. Investing in private company equity carries significant risk, including illiquidity and potential total loss of investment. Consult a qualified financial advisor before making investment decisions.

Conclusion

From a UC Berkeley research project in 2013 to a $62 billion private company in 2024, Databricks has built the most valuable independent data infrastructure business in the world on four compounding advantages: an open-source foundation in Apache Spark that gave it a global developer base before the first enterprise sale, Data Lakehouse category leadership that captured workloads across data engineering and analytics, a well-timed pivot into enterprise generative AI through the MosaicML acquisition, and $14 billion in capital backing from the most prominent investors in enterprise software.

The valuation multiple story — from ~28x ARR at Series D to ~47x at the 2021 peak to ~25x at the Series J — reflects both the macroeconomic forces that shaped the SaaS cycle and the AI-driven re-expansion that brought Databricks to its current position. As the enterprise AI adoption wave accelerates, Databricks sits at a critical intersection of data infrastructure and AI development, a market position that will likely define both its near-term revenue trajectory and the terms of its public market debut, whenever that arrives.

This article is updated as material changes occur, including new funding rounds, IPO filings, and significant revenue disclosures. The most recent update reflects Databricks' December 2024 Series J round. For real-time funding data, refer to Crunchbase.