Key facts
- Databricks secured a new funding round, achieving a valuation of $188 billion.
- The funding round was led by Coatue.
- The company's valuation has significantly increased over the past 18 months.
- Databricks has successfully rebranded itself as an AI solutions provider.
- Internal benchmarking indicates cost-effectiveness of open-weight AI models for coding.
Databricks announced a new funding round that values the company at $188 billion, led by Coatue. While the exact amount raised has not been disclosed, it is expected to close later this summer, with reports suggesting around $3 billion. This valuation marks a significant increase from its previous rounds, reflecting its successful transition from a big data company to a prominent AI provider.
Over the past approximately 18 months, Databricks has seen its valuation climb dramatically. In February, it closed a $5 billion Series L round at a $134 billion valuation. Prior to that, in September 2025, it raised $1 billion at a $100 billion valuation, and in December 2024, it secured a record $10 billion at a $62 billion valuation.
Founded in 2013, Databricks initially gained prominence in the big data era with software for cloud-based data storage and analytics. Its existing infrastructure for enterprise data positioned it well to meet the growing demand for AI solutions with the security and governance expected by businesses.
The company has been actively developing and rolling out AI products, including Lakebase, a database for AI agents, and Unity, an AI gateway. It has also gained recognition for adopting and championing cost-effective, open-weight AI models, such as Z.ai's GLM 5.2, for tasks like coding.
Databricks CEO Ali Ghodsi recently shared internal benchmarking results comparing AI model costs for its 3,000 software engineers. The findings indicated that open models, particularly GLM 5.2, are capable of handling complex coding tasks at a lower total cost than proprietary models from Anthropic and OpenAI. The study also highlighted the significant impact of agentic coding tools, or 'harnesses,' on cost management, with open-source options like Pi proving effective in managing context and reducing expenses without sacrificing quality.