Databricks' $10B Deal: Insight VC on the Acquisition and CEO's Missteps
Databricks Secures $10 Billion in Funding
Investors demonstrated significant enthusiasm this week, actively seeking participation in Databricks’ unprecedented $10 billion fundraising round, as detailed by a leading venture capitalist to TechCrunch.
George Mathew, managing director at Insight Partners, recounted the intense activity surrounding the deal. He noted that discussions extended late into the night, a testament to the exceptional nature of the opportunity. Insight Partners, alongside Thrive, Joshua Kushner’s firm, spearheaded the investment, with the majority being existing investors.
Insight Partners' Role in the Deal
Mathew explained that Insight Partners actively pursued a co-lead position, despite already having an investment in Databricks. This required leveraging the Insight Partners Public Equities fund, managed by John Wolff, which is dedicated to acquiring public stocks.
The level of interest was substantial, leading to a rapid increase in both the allocation and the company’s valuation. Initial estimates in mid-November placed the deal around $8 billion.
Within days, this figure rose to $9.5 billion, reflecting a $60 billion valuation. Ultimately, the round concluded at $10 billion, establishing a $62 billion valuation for Databricks.
Comparison to Other Major Funding Rounds
This funding surpasses OpenAI’s $6.6 billion raise in October, which previously held the record for the largest venture round ever.
Mathew emphasized the strong institutional demand for a company he described as “generational.” Having focused on data, AI, and ML investments at Insight for the past four years, he expressed his excitement about this particular opportunity.
Details of the Investment
The investment included a significant secondary tender offer, allowing Databricks employees and existing investors to sell shares. New preferred shares were also issued to the new investor.
Databricks characterized the $10 billion raise as “nondilutive,” suggesting a substantial portion came from the secondary offering.
From Big Data Feature to Data Warehouse Leader
Founded in 2013, Databricks’ journey could have taken a different path. The company’s initial technology, Spark, was instrumental in the “big data” trend of the past, enabling fast analysis of in-house data.
However, with the shift towards cloud-based data storage, Databricks initially processed data before passing it on to other providers. This raised concerns about the company’s long-term relevance.
Seeking Guidance and Pivoting to Data Warehousing
Databricks co-founder and CEO Ali Ghodsi sought advice from Mathew, who previously served as COO of big data company Alteryx. The two had a long-standing relationship.
“Ali consulted me regarding a potential entry into the data warehousing market,” Mathew recalled. “I initially considered it a misguided idea, but I was demonstrably incorrect.”
Traditional data warehouse vendors were already facing challenges from emerging cloud-based solutions like Snowflake and AWS’ Redshift.
The Launch of Databricks SQL
Despite these challenges, Databricks launched Databricks SQL in late 2020, quickly establishing itself as a significant competitor to Snowflake.
The subsequent rise of large language models (LLMs) further fueled Databricks’ growth, as these models require access to high-quality enterprise data. Mathew stated that Databricks is poised to become a primary source of this data for enterprises.
Future Outlook and Financial Performance
As of late 2024, with the IPO market remaining constrained, investors are actively seeking opportunities in AI infrastructure, particularly data warehouses capable of supporting LLMs.
Databricks projects a $3 billion revenue run rate by the end of its fiscal fourth quarter, with Databricks SQL contributing a $600 million revenue run rate, representing a 150% year-over-year increase.
