Databricks Boosts AI Agent Business With $1 Billion Neon Purchase

Data and artificial intelligence (AI) firm Databricks is acquiring database startup Neon.

“As the $100-billion-plus database market braces for unprecedented disruption driven by AI, Databricks plans to continue innovating and investing in Neon’s database and developer experience for existing and new Neon customers and partners,” the company said in a Wednesday (May 14) news release.

While the company did not list a dollar amount for the acquisition, a report by The Wall Street Journal (WSJ) values the deal at around $1 billion.

Databricks notes in its release that AI agents are becoming increasingly important to modern developers, adding that Neon is “purpose-built to support their agentic workflows.”

Recent in-house telemetry showed that more than 80% of the databases provisioned on Neon were created automatically by AI agents and not by humans, underlining the explosive growth of agentic workloads.

“The era of AI-native, agent-driven applications is reshaping what a database must do,” Databricks Co-founder and CEO Ali Ghodsi said in the release.

“By bringing Neon into Databricks, we’re giving developers a serverless Postgres that can keep up with agentic speed, pay-as-you-go economics, and the openness of the Postgres community,” Ghodsi added, referring to the PostgreSQL open-source database.

Speaking to the WSJ, Ghodsi said that “pretty much every customer we have wants to leverage agents.” However, those agents need to be able to build new databases to support what they do, which is where Neon comes in.

Databricks was valued at $62 billion earlier this year in a Series J funding round, taking in $10 billion in equity financing along with a $5.25 billion credit facility from several banking giants.

Meanwhile, PYMNTS wrote earlier this week about the rise of the agentic AI web experience, arguing that it “could mark a transformative period in how users access and interact with information online.”

At the center of this potential evolution are large language models (LLMs) such as OpenAI’s GPT-4, Google’s Gemini, and Anthropic’s Claude.

These systems are increasingly able to understand context, maintain memory, and execute multi-step tasks. Still, true agency requires integration, not just linguistic prowess. Application programming interfaces (APIs) now act as conduits that let AI agents interact with apps, services and devices.

“For businesses, agentic AI presents a double-edged sword,” that report said. “On one hand, it might open new avenues for customer engagement, operational efficiency and product innovation. On the other, it may also threaten to disrupt long-standing business models.”

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