Author: Cora Xu, Edited by Manman Zhou
The AI Financing Boom Continues.
This is likely the largest-ever venture capital round in Silicon Valley history. AI data analytics platform Databricks announced today that it is raising $10 billion in a Series J funding round led by Thrive Capital, which upon completion, will value Databricks at $62 billion.
The institutions participating in this round are very prestigious, including not only Thrive Capital but also Andreessen Horowitz, DST Global, GIC, Insight Partners, and WCM Investment Management as co-leaders. Other significant participants include existing investors Ontario Teachers’ Pension Plan and new investors ICONIQ Growth, MGX, Sands Capital, and Wellington Management.
Databricks plans to invest this capital in new artificial intelligence products, acquisitions, and a significant expansion of its international market business. In addition to driving its growth, the funds are expected to be used to provide liquidity for current and former employees and to pay related taxes. Finally, this quarter marks the company’s first expectation of achieving positive free cash flow.
As of October 31, 2024, Databricks’ third quarter saw year-over-year growth of over 60%. The company expects a revenue run rate of over $3 billion and positive free cash flow as of January 31, 2025.
At the same time, the company has more than 500 customers with a revenue run rate of over $1 million per year, and its intelligent data warehouse product, Databricks SQL, has a revenue run rate of $600 million, with year-over-year growth of over 150%.
A Luxurious Investment Team Joins Hands to Create the Largest Funding Round in History
“It’s been a crazy week,” said a venture capitalist who led the deal, revealing that investment firms are participating in this round of high-stakes betting, and Databricks’ financing amount is growing rapidly.
In mid-November, media reported that Databricks’ financing was expected to reach around $8 billion. A few days later, Databricks’ financing deal reached $9.5 billion, with a valuation of $60 billion. As of today, the financing deal has reached $10 billion, with a valuation of $62 billion. According to CB Insights, Databricks’ valuation is only behind a few non-public companies such as OpenAI and SpaceX.
Regarding the financing process, George Mathew, Managing Director of Insight Partners, laughed and said, “Some phone meetings went very smoothly, but that’s okay, that’s how good opportunities arise.”
Some media also disclosed more detailed investment details. Insight Partners, as one of the largest investors in Databricks this year, invested about $1 billion. The company stated that adopting generative artificial intelligence is the main catalyst for Databricks’ next phase of growth.
In November, Bloomberg reported that Thrive Capital was negotiating to acquire about $1 billion worth of Databricks’ shares.
Among them, the large fund known for public investments, **WCM Investment Management**, is also a co-leader in this round of financing, investing **$400 million to $500 million**. The company recruited investor Alan Tu from T. Rowe Price earlier this year to lead private investment operations.
A sovereign wealth fund based in Abu Dhabi, **MGX**, also invested a similar amount – close to **$500 million**. MGX stated that it would invest $100 billion in AI projects, and this is just a small part of it.
Capital Group is also expected to invest at least **$300 million** in Databricks. Headquartered in Los Angeles, Capital Group, with a history of 93 years, manages $2.7 trillion in assets and is known for large-scale investments in large public companies, having invested in Waymo and Stripe.
It is reported that Lightspeed Venture Partners also participated in this transaction. An unnamed知情人士 said that the company invested **$200 million** in this round of financing.
In addition, other large mutual funds such as Fidelity, T. Rowe Price, Franklin Templeton, and BlackRock also invested in Databricks at a lower entry price.
Currently, Databricks has raised funds from almost all other mutual funds, related strategic investors (Nvidia, Amazon), and a large number of hedge funds, pension funds, and endowment funds, completing **$8.6 billion** in financing.
From the existing financing details, we can see that there are still many investment institutions that can promote the completion of huge financing. At the same time, this also indicates the vigorous development of the venture capital industry.
When venture capital firms invest in a company like Databricks, which has been around for ten years and has raised funds up to the J round, what kind of returns can they really expect?
Reports say that Databricks needs to have a sensational initial public offering within a few years to satisfy everyone. Investors expect Databricks not to delay the IPO date for more than a few years.
Databricks co-founder and CEO Ali Ghodsi said, “In theory, the earliest we could go public is next year. But this (round of financing) provides us with some flexibility to provide liquidity opportunities for employees.”
John Wolff of Insight Partners said that Databricks’ growth rate is twice that of any public company and has already achieved a breakeven. “If you assume the same growth rate, then its pricing is more attractive than the stocks of other public companies on the market.” Insight Partners first invested in Databricks three years ago and is now increasing its investment because they believe that buying more Databricks stocks can yield better financial returns than acquiring similar public companies.
Databricks’ employees are obviously also benefiting a lot from this “non-dilutive” $10 billion financing round, as employees or other existing investors can sell shares, and Databricks issued new preferred shares to new investors.
7 Ph.D. Students Start a Business for 11 Years, 3 Have Become Billionaires
Databricks was founded in 2013 by seven Ph.D. students from the University of California, Berkeley, mainly selling artificial intelligence, big data analysis, and cloud tools to help companies build data and artificial intelligence-driven applications. The company has been established for eleven years.
According to the company’s valuation, Forbes predicted that at least Ali Ghodsi, Ion Stoica, and Matei Zaharia, three of the founding team, have become billionaires.
Among them, Ali Ghodsi serves as the CEO and co-founder of Databricks, mainly responsible for the company’s development and international expansion.
Before becoming the CEO in January 2016, Ali Ghodsi served as the vice president of engineering and product management at the company and was also one of the creators of the open-source project Apache Spark. In addition to working at Databricks, Ghodsi Ali also serves as an adjunct professor at the University of California, Berkeley, and a board member of the RiseLab at the University of California, Berkeley.
Interestingly, at the beginning of the establishment, Ghodsi sought advice from his friend Mathew, mentioning that he wanted to enter the database market. At that time, Mathew served as the chief operating officer of the big data company Alteryx. “At that time, I told him that this was the stupidest idea I had ever heard,” Mathew said, “Fortunately, he did not listen to me, nor did he blame me for it.”
Reynold Xin is the only Chinese-American co-founder of Databricks, serving as the co-founder and chief architect. Reynold initiated projects such as DataFrames and Project Tungsten. To demonstrate Spark’s scalability and performance, he led the 2014 Daytona GraySort competition and set a world record that year, breaking the previous record by 30 times the efficiency per node. Before joining Databricks, he was a Ph.D. student at AMPLab at the University of California, Berkeley, focusing on scalable data processing. He wrote the most cited papers at SIGMOD 2011, 2013, and 2015 and won the best demonstration awards at VLDB 2011 and SIGMOD 2012.
Matei Zaharia is the Chief Technology Officer and co-founder of Databricks, as well as an associate professor of computer science at the University of California, Berkeley. He launched the Apache Spark project in 2009 while pursuing his Ph.D. at the University of California, Berkeley, and participated in the development of other widely used data and AI software, including MLflow, Delta Lake, and DBRX.
Zaharia has researched combining large language models (LLM) with external data sources (such as search systems) and improving their efficiency and result quality. Zaharia’s research won the 2014 ACM Doctoral Dissertation Award and the Presidential Early Career Award for Scientists and Engineers.
Direct Competition with Snowflake, Numerous Customers
Databricks initially was the commercialization project of the Spark big data processing system from the AMP Lab at the University of California, Berkeley.
The big data tool Spark, which Databricks first created, can help companies analyze their internal big data at an extremely fast speed, which also allowed it to gain a foothold in Silicon Valley. At that time, traditional data warehouse vendors (who store and analyze large amounts of corporate data) also competed with emerging cloud computing companies like Snowflake and products from cloud vendors like AWS’s Redshift.
By the end of 2020, Databricks launched its data warehouse product – Databricks SQL and quickly became a strong competitor to Snowflake.
With an understanding of AI data, Databricks has successively created Apache Spark, Delta Lake, MLflow, and OneLakehousePlatform, opening multiple product lines. Databricks’ products are mainly provided on cloud services such as AWS, Azure, and GCP.
Currently, Databricks mainly develops software to extract, analyze, and build artificial intelligence applications that use complex data from various sources. In terms of business models, Databricks charges customers based on the amount of computing resources consumed per second and has created its own DBU as a unit of measurement.
From the official website’s customer resource pool, Databricks has more than 500 customers, including mobile communication company AT&T, electronic product company HP, and language AI tool Grammarly.
Regarding this round of financing, Databricks CEO Ali Ghodsi said in an interview that maintaining this growth rate means expanding Databricks’ market operations and engineering talent. As for potential acquisitions, Ghodsi said he is looking for artificial intelligence startups to find technology and talent.
Currently, Databricks has 7,000 employees and is expected to achieve positive free cash flow for the first time in the quarter ending January 31st, with a revenue run rate exceeding $3 billion. Sources revealed that the company also expects to achieve $3.8 billion in revenue in the next fiscal year.
However, in the context of intensifying AI competition, Databricks also faces competition from cloud providers and needs to develop new business lines and maintain rapid growth.
