Databricks valuation skyrockets to $43bn after $500m funding round


Databricks, a leading analytics and AI platform, announced today that it has successfully raised $500m in a new funding round.

The round was led by T. Rowe Price Associates, joined by new investors Nvidia and Capital One Ventures.

Founded in 2013 by the original creators of Apache Spark, Databricks has made a name for itself with its unique “lakehouse” platform. This platform combines the functionalities of data warehouses and data lakes, unifying data, analytics, and AI on a single cloud-based platform. Customers can govern, manage, and derive insights from their enterprise data more effectively, accelerating their AI and analytics projects.

Databricks CEO Ali Ghodsi stated that the fresh funds will focus on deepening strategic partnerships and accelerating value. Particularly, the partnership with Nvidia aims to enhance various elements of Databricks’ platform, from the GPUs that underpin the AI applications to the software running on top of them.

Additional details highlight that Databricks had a strong second quarter in 2023. The company reported its highest-ever quarterly incremental revenue growth, acquired MosaicML, a generative AI platform, and boasted more than 10,000 global customers. Furthermore, the firm has recently been in the media spotlight, with speculation regarding its significant cash burn and its potential for an IPO.

Ali Ghodsi noted, “This is not like we need cash. Our poor finance team was just looking at doing the strategic partnership…because of the leaks, now everyone wants to invest.” Ghodsi added that the enterprise sector is now ripe for an explosion of B2B generative AI applications, stating, “I think Databricks is really well-positioned to do that because we already have all the data of these large enterprises and they already trust us to keep it safe and private and confidential.”

Before this round, Databricks had already made a mark in the FinTech world by releasing open science-based large language models like Dolly and Dolly 2.0, aimed at enterprise use.

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