Databricks: $188 Billion from AI, a Meteoric Success

Databricks Reaches a Valuation of $188 Billion

Databricks announced on Thursday a new funding round that values the company at an impressive $188 billion. This round was led by Coatue, a well-known investor in the tech sector.

Although Databricks has not yet specified the exact amount raised, it indicated that the funds are not yet in its possession and that the closing of the funding round is expected later this summer. According to some sources, the fundraising would amount to approximately $3 billion. It is unusual for a company to make an announcement before receiving the funds, but a venture capital investor told TechCrunch that the deal is solid. In fact, many firms are eager to participate, allowing Databricks to be open about its new valuation.

An Impressive Funding Journey

Databricks has experienced a remarkable funding trajectory over the past eighteen months. The company has successfully repositioned itself as an AI provider, moving beyond its former image as a SaaS sensation. This shift dates back to the BC (Before ChatGPT) era.

Just five months ago, in February, Databricks closed a $5 billion funding round in a Series L, reaching a valuation of $134 billion at that time. Five months prior, in September 2025, it raised $1 billion at a valuation of $100 billion. And about nine months before that, in December 2024, the company had a record funding round of $10 billion at a valuation of $62 billion.

A Strategic Transformation

The frequency of Databricks' fundraising has even inspired memes about exhausting the letters of the alphabet for naming funding rounds. "Activating alerts for when we have a Series AA," one person posted.

However, this transformation of Databricks' image is very real. Founded in 2013, the company initially thrived in the big data era, offering software solutions that allowed businesses to store massive amounts of data in the cloud while providing rapid analytics.

AI at the Core of the Strategy

With an already massive enterprise database, Databricks was ideally positioned to meet the growing demand for AI while ensuring the security and governance expected from traditional enterprise software.

The company began launching a series of AI products, such as Lakebase, a database designed for AI agents, and Unity, an AI gateway, as well as a "meta-harness" called Omnigent that manages multiple agents.

Adoption of Open-Weight Models

Databricks also distinguished itself by adopting open-weight models based in China, a major trend of 2026. These models, whose source code is accessible to all for use and modification, allow for cost control. Databricks is particularly adept at the GLM 5.2 model from Z.ai for coding.

Last week, Databricks CEO Ali Ghodsi shared the results of internal benchmarks for managing AI costs for its 3,000 software engineers.

Comparison of AI Models

The company compared various AI models on real tasks performed by its programmers. In a blog post, Databricks revealed that "open models, and GLM 5.2 in particular, are now capable of handling even the most complex coding tasks" while being less expensive than proprietary models from Anthropic and OpenAI.

It was also surprising to discover that the choice of harness, a coding agent tool like Codex or Claude Code, influenced costs. Databricks found that the open-source harness Pi was among the best for managing the context of each prompt, making it one of the most economical options without compromising quality.

The blog post concluded that the choice of model is just one piece of the puzzle, highlighting the importance of the harness in cost management.

A Promising Future

All these factors have contributed to strengthening Databricks' image as an AI company, even though it was not founded as an AI lab. This strategic positioning has allowed it to raise funds and increase its valuation. The AI effect is so powerful today that even unexpected companies, like the sandwich chain Jersey Mike’s, mention AI 22 times in their S-1 filings.