Databricks hits $188B valuation on $3B raise

Key Takeaways

• Databricks reached a $188 billion valuation, up from $62 billion in December 2024
• The company raised roughly $3 billion in a round led by Coatue, its fourth major raise in 18 months
• Databricks credits its valuation jump to repositioning as an AI company with products like Lakebase and its AI gateway Unity

Databricks announced a new funding round on Thursday that values the company at $188 billion. Coatue led the round. The company did not disclose the exact amount raised, though reports peg it at roughly $3 billion. The deal has not closed yet, but a VC source told TechCrunch that so many firms wanted in that Databricks saw no reason to keep the number quiet.

This marks the fourth major raise for Databricks in 18 months. In February, the company closed a $5 billion Series L at $134 billion. In September 2025, it raised $1 billion at $100 billion. And in December 2024, it raised what was then a record $10 billion at $62 billion. The company has run through so many funding letters that the announcement became meme fodder.

How did Databricks triple its valuation so fast?

Founded in 2013, Databricks grew during the big data era on software that let enterprises store massive datasets in the cloud while still getting fast analytics. That positioning turned out to be prescient. Because the company already sat on troves of enterprise data, it was well placed when customers started demanding AI with the same security and governance they expected from traditional enterprise software.

The company leaned into this. It rolled out Lakebase, a database built for AI agents. It launched Unity, an AI gateway. And it shipped Omnigent, a harness that manages multiple agents. Each product reinforced the message: Databricks is not just a data company, it is an AI company.

Databricks also became a visible champion of open-weight models from Chinese labs. In particular, it has pushed Z.ai's GLM 5.2 for coding tasks. Last week, CEO Ali Ghodsi published internal benchmarks showing that open models can handle high-difficulty coding at lower total cost than proprietary models from Anthropic and OpenAI.

The harness matters as much as the model

Databricks' internal benchmarking produced a second finding that surprised some observers: the choice of agentic coding harness, the tool that wraps around a model and manages its context and instructions, impacted costs as much as the choice of model itself.

The company tested harnesses like Codex and Claude Code. It found the open-source harness Pi to be one of the best at managing context per prompt, resulting in lower costs without sacrificing quality. "The lesson here isn't that one harness is always cheaper or that native harnesses are worse," the company wrote. "Instead, model choice is only one piece of the puzzle."

For SaaS operators running AI workloads, this is a practical takeaway. Optimizing spend is not just about picking a cheaper model. It is about the entire stack, from model selection to the harness that orchestrates prompts to the infrastructure underneath.

Why investors keep writing checks

Private market valuations have become highly sensitive to the AI label. TechCrunch noted that even Jersey Mike's mentioned AI 22 times in its S-1 documents. For Databricks, the AI repositioning is more than branding. The company has shipped products, published benchmarks, and built a narrative around cost-conscious enterprise AI adoption.

That narrative resonates with investors who want exposure to AI infrastructure without betting on a single model provider. Databricks sits between the model layer and the enterprise data layer, a position that looks increasingly valuable as companies realize they need both.

Whether $188 billion is the right number is another question. At this valuation, Databricks would need to grow into one of the largest enterprise software companies ever built. But in the current funding climate, being seen as an AI company, rather than a data company, is enough to keep the checks coming.

Frequently Asked Questions

How much did Databricks raise in its latest round?

Databricks has not disclosed the exact amount, but reports indicate the round is roughly $3 billion. The round is led by Coatue and is expected to close later this summer.

What is Databricks' current valuation?

The new funding round values Databricks at $188 billion, up from $134 billion in February 2026 and $62 billion in December 2024.

Why is Databricks valued so highly?

Databricks has repositioned from a big data analytics company to an AI infrastructure company. It has launched AI-specific products like Lakebase and Unity, and it controls enterprise data that companies need for AI workloads.

What is Databricks' Omnigent product?

Omnigent is a harness that manages multiple AI agents. It is part of Databricks' suite of AI products aimed at enterprises running agentic workflows.

Is Databricks profitable?

Databricks has not disclosed recent profitability figures. The company has focused on growth and has raised over $19 billion in funding across multiple rounds.

Source: Enterprise News | TechCrunch / Julie Bort