Insight VC describes the massive $10 billion Databricks deal and the bad advice the CEO ignored

It’s been a tough week for investors navigating their way into Databricks’ record-breaking $10 billion fundraising, one of the venture capitalists who led the deal told TechCrunch.

“There were calls made late at night, and that’s OK, that’s how good opportunities appear,” George Matthew, managing director at Insight Partners, described with a smile. Along with Thrive’s new investor, The Joshua Kushner Company, Insight was one of the six companies that led the deal. All of them except Thrive were existing investors.

“We worked to make sure we could be a co-leader, even though we were already an investor at the cap table,” Matthew said. Insight first invested in Databricks in 2021. But to get into this massive deal, Insight had to tap into the Insight Partners Public Equities fund, which was created to buy public stocks, under managing director John Wolfe.

There was so much rabid interest that allocation — and valuation — skyrocketed. In mid-November, the deal was on track to be worth about $8 billion. Reuters reported at that time. A few days later, it reached $9.5 billion at a $60 billion valuation, and by Tuesday, It closed at $10 billion with $62 billion evaluation.

For perspective, this is more than OpenAI raises $6.6 billion in Octoberthe biggest adventure tour ever.

“There was a lot of institutional demand and interest in Generations,” Matthew said. “I’ve been an investor in Insight for the past four years in all things data, AI, and machine learning. This is something I live for.”

The investment included a large secondary tender offer, where Databricks employees or other existing investors could sell shares. New preferred shares are issued to the new investor. Databricks did not specify the amount of the secondary increase, other than to describe the $10 billion as “undiluted,” which implies a good portion.

Interestingly, Databricks, founded in 2013, could have been a tragic story. A decade ago, its founders created a technology, Spark, that was central to the “big data” trend of the past year. Spark has helped organizations analyze their internal big data at breakneck speed.

With the advent of data hosted in the cloud, the company would process the data and then deliver it to other players. It could have found itself slowly moving to an irrelevant big data feature.

Ali Ghodsi, co-founder and CEO of Databricks (pictured), sought advice from Matthew, who ran big data company Alteryx as COO before becoming a venture capitalist. The two have been friends since the early days of Databricks.

“Ali called me a few years ago and said, ‘Hey, I’m thinking about getting into the data storage market.’ And I just said, ‘That’s the stupidest idea I’ve ever heard.’” Matthew laughs, adding that he’s glad Qudsi didn’t listen to him, and didn’t hold his bad advice against him. .

At the time, traditional data warehouse vendors — which store massive amounts of enterprise data used for analytics — were also struggling against the likes of rising cloud stars like Snowflake and cloud vendor-owned products, like AWS’s Redshift.

But in late 2020, Databricks has been launched Its own data warehouse product anyway – Databricks SQL – quickly became a major competitor to Snowflake.

Then came large language models (LLMs), constantly hungry for high-quality enterprise data. “Where does this high-quality data come from? For enterprises, it will come from somewhere like Databricks,” Matthew said.

Fast forward to the end of 2024, with the IPO market still closed and investors wanting a piece of AI infrastructure products, such as data warehouses that could serve LLM holders.

Databricks says That by the end of the fourth fiscal quarter, it will have a revenue run rate of $3 billion, with a revenue run rate of $600 million for Databricks SQL, up 150% for the year.