DatabricksがAI企業として1880億ドルの評価額を達成Databricks hits $188B valuation, extending its run as AI’s favorite second act

Databricks has reached a valuation of $188 billion in a new funding round, according to a report from TechCrunch, a milestone that further establishes the data-and-AI company as one of the most valuable privately held businesses in the sector. The figure matters because it reflects how aggressively investors continue to back the infrastructure layer beneath the current wave of artificial intelligence, rather than only the consumer-facing models and applications that draw the most attention.

The scale of the valuation represents a steep climb for the company. Databricks closed a large late-stage round in December 2024 that valued it at roughly $62 billion, and its worth has risen sharply through subsequent financing. A move to $188 billion, if confirmed by the company, would place Databricks among a small group of private firms whose paper valuations rival or exceed those of many established public technology companies. As with all private-market valuations, the figure is set by negotiation between the company and its investors and should not be read as equivalent to a market price that public trading would produce.

Databricks built its business around what it calls the "lakehouse" architecture, a design that merges the low-cost, flexible storage of a data lake with the structured querying and governance features traditionally associated with a data warehouse. The company was founded by the original creators of Apache Spark, the open-source engine for large-scale data processing, and it has since contributed to or commercialized a range of related technologies, including Delta Lake for reliable data storage, MLflow for managing machine-learning workflows, and Unity Catalog for data governance. These tools position the company as a place where organizations store, clean, and analyze the large datasets that machine-learning systems depend on.

The pivot toward being described as an "AI company" has been deliberate and is central to the valuation story. In 2023 Databricks acquired MosaicML, a startup focused on training and deploying generative models, in a deal reported at around $1.3 billion. That acquisition became the foundation of its Mosaic AI product line, which lets customers build, fine-tune, and serve models using their own proprietary data. The strategic logic is that enterprises increasingly want to apply large language models to their internal information while keeping that data within their own governed environments, and Databricks aims to be the platform where both the data and the models live.

The company's rise plays out against intense competition. Its closest rival is Snowflake, a publicly traded data-warehousing firm that has similarly expanded into AI features and model hosting. Databricks also competes, and in some cases partners, with the major cloud providers, Amazon Web Services, Microsoft Azure, and Google Cloud, all of which offer overlapping data and AI services. To strengthen its position on open data formats, Databricks acquired Tabular, a company founded by the creators of Apache Iceberg, an increasingly popular table format, in a move that appeared aimed at bridging competing standards in the data ecosystem.

The funding also fits a broader pattern of extraordinary capital flowing into AI infrastructure. Model developers such as OpenAI and Anthropic have raised enormous sums, while chipmaker Nvidia has seen its market value surge on demand for the processors used to train and run large models. Databricks sits one layer removed from that hardware and model race, supplying the data pipelines, governance, and tooling that companies need before AI can be deployed usefully. Investors appear to be betting that this "picks and shovels" role will remain valuable regardless of which specific models ultimately dominate.

Several questions remain. Large private valuations depend on continued enterprise spending on AI, which some analysts caution could moderate if returns on those investments prove slower to materialize than expected. A valuation of this size also raises expectations about an eventual initial public offering, though Databricks has not committed to a timeline, and the company has repeatedly said it prefers to remain private while it grows. For now, the round signals sustained investor confidence in the data infrastructure underpinning enterprise AI, even as the wider market weighs how durable the current spending cycle will prove to be.