Databricks Raises $1B to Challenge AI Database Market

Databricks Secures New Funding at $100 Billion Valuation

Recent reports confirm that Databricks is finalizing a new investment round, achieving a valuation of $100 billion. This information was initially published by the Wall Street Journal and has been corroborated by sources speaking with TechCrunch.

Details of the Funding Round

According to an exclusive source, the round totals approximately $1 billion and experienced significant oversubscription. Databricks, a leading provider of data analytics solutions, deliberately limited the amount of equity offered, as current operations are well-funded following a previous $10 billion raise at a $62 billion valuation in January. (OpenAI subsequently surpassed this with a $40 billion raise in March.)

Thrive and Insight Partners, both previous investors, co-led this funding round, mirroring their leadership in the prior investment. Since its founding in 2013, the company has now accumulated around $20 billion in funding.

Employee Share Sales

This was a primary funding round, meaning no existing shares were sold by employees. However, sources indicate that Databricks facilitated two secondary offerings for employees in 2025.

These offerings allowed employees to sell between 40%, 50%, or 60% of their shares, contingent on their individual holdings.
In both instances, the full allocation of funds for the secondary round wasn't fully utilized, suggesting employees retained a larger portion of their shares than initially anticipated.

While an IPO isn’t imminent, these secondary rounds provided employees with opportunities to realize gains from their equity.

Strategic Investments with New Capital

Databricks co-founder and CEO Ali Ghodsi explained to TechCrunch that the new funding will be directed towards two key initiatives: a database specifically designed for AI agents and the company’s AI agent platform.

The company plans substantial investment in its AI agent database, making it broadly accessible to all customers. Launched as Lakebase at their annual tech conference in June, this product is built on the open-source Postgres database and caters to the needs of enterprise developers engaged in vibe-coding projects, positioning it as a competitor to Supabase.

Addressing the Database Market

Ghodsi highlighted the substantial size of the database market, estimating a total addressable market (TAM) of $105 billion. He noted a historical lack of significant change in this market for the past four decades, implicitly referencing Oracle’s long-standing dominance.

He shared a compelling statistic: a year ago, 30% of new databases were created by AI agents, a figure that has risen to 80% this year. He anticipates this trend will continue, reaching 99% within the next year.

“The emerging user is not human; it’s an AI agent,” Ghodsi stated. “Focusing on the success of this user profile is the key to disrupting the existing TAM.”

Lakebase’s Differentiation

Regarding Lakebase’s competitive advantage over existing Postgres-based databases, Ghodsi emphasized the concept of “separated compute and storage.”

By decoupling expensive compute resources from lower-cost storage, Databricks can enable users to create numerous databases affordably. This is particularly important given the rapid database creation rate of AI agents, preventing excessive costs.

Agent Bricks: Focusing on Practical AI

The second major investment area is Agent Bricks, Databricks’ AI agent platform, also unveiled in June. Ghodsi dismissed the focus on “superintelligence,” arguing that organizations require different capabilities.

Instead of seeking artificial general intelligence, companies need agents capable of autonomously handling routine tasks, such as employee onboarding or providing personalized HR benefits information.

Ghodsi believes this pragmatic approach presents a larger opportunity for global GDP and organizational efficiency, providing Agent Bricks with a distinct competitive edge.

The additional funding will also support Databricks in attracting top AI talent, acknowledging the current high demand and associated costs.

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