Databricks Soars to $188 Billion Valuation, Establishing Itself as AI’s Premier Follow-Up Player
On Thursday, Databricks revealed a new funding round that has elevated its valuation to $188 billion, with Coatue leading the investment.
While the exact amount raised has not been disclosed, the company mentioned that the funds have not yet been received and will finalize later this summer. Reports indicate that the funding could be around $3 billion. It is uncommon for a company to announce such news before securing the funds, but insiders suggest that the deal is robust, prompting Databricks to share its impressive new valuation.
Databricks has experienced a continuous fundraising spree over the past 18 months, successfully shifting its image to become recognized as an AI leader rather than just a former SaaS pioneer. This transition marks a significant change since prior to the rise of AI technologies like ChatGPT.
Earlier this year, in February, Databricks secured a $5 billion Series L funding round at a $134 billion valuation. Five months earlier, in September 2025, it raised $1 billion at a valuation of $100 billion. Before that, in December 2024, the company achieved a record-breaking $10 billion round at a valuation of $62 billion.
Given the number of fundraising rounds it has completed, this latest milestone has sparked memes regarding the limitation of alphabet letters for naming future rounds. One user humorously commented about needing to watch for a “Series AA.”
Founded in 2013, Databricks initially thrived during the big data boom, providing cloud software solutions that enabled businesses to handle vast amounts of data and perform rapid analytics.
With extensive access to enterprise data, the company was ideally positioned to meet the growing demand for AI solutions that ensure the same level of security and governance as conventional enterprise software.
The firm has rolled out various AI products, including Lakebase, designed for AI agents, and Unity, which acts as an AI gateway. They also introduced Omnigent, a meta-harness that optimizes the management of multiple agents.
Additionally, Databricks has become a leading example of companies using more cost-effective, open-weight models developed in China, a significant trend of 2026. Particularly, it has endorsed Z.ai’s GLM 5.2 as a coding standard.
Recently, CEO Ali Ghodsi disclosed results from internal benchmarking aimed at managing AI expenses for the company’s 3,000 engineers.
In these benchmarks, Databricks evaluated AI models against the actual tasks performed by its programmers. The findings suggested that “open models, particularly GLM 5.2, excel at handling even the most complex coding challenges” while also being more cost-effective than proprietary models from competitors like Anthropic and OpenAI.
Unexpectedly, the study also revealed that the choice of coding tool—like Codex or Claude Code—significantly influences the costs. An open-source tool named Pi stood out for effectively managing context around prompts, proving to be one of the most economical options without compromising quality.
The key takeaway emphasized by Databricks was that the choice of model is a crucial aspect, but not the only factor affecting costs.
All these advancements have reinforced Databricks’ reputation as an AI entity, despite its original foundation not being focused on AI. This shift has significantly aided in attracting investments and boosting its valuation. As observed, the current AI trend is so influential that even companies like Jersey Mike’s referenced AI numerous times in their S-1 filings.
