Image source: Generated by Unbounded AI

Zhidongxi reported on December 18 that a single round of financing exceeded 70 billion yuan! Nearly 90% of the financing has been completed, which is a new record for global AI startup financing.

Databricks, an AI data analysis company, announced that its Series J financing target is US$10 billion (approximately RMB 72.8 billion), and has currently completed US$8.6 billion (approximately RMB 62.6 billion), surpassing OpenAI in It received US$6.5 billion in financing (approximately RMB 47.3 billion) in October.

This round of financing was led by Thrive Capital, with participation from well-known investment institutions such as Andreessen Horowitz, DST Global, GIC, Insight Partners and WCM Investment Management.

This financing brings Databricks’ valuation to US$62 billion (approximately RMB 451.7 billion), a significant increase from US$43 billion (approximately RMB 313.3 billion) in 2023, leading Compared to its main competitor Snowflake, the latter’s latest market value is approximately US$57 billion (approximately RMB 415.2 billion).

▲Databricks annual recurring revenue (ARR) changes (Source: SACAR)

Databricks also disclosed the following key data:

1. As of 2024 In the third quarter ending on October 31, the year-on-year growth exceeded 60%;

2. In the fourth quarter ending on January 31, 2025, revenue is expected to The run rate will exceed US$3 billion (approximately RMB 21.9 billion), and free cash flow will be positive for the first time;

3. Non-GAAP subscription gross profit margin continues to remain above 80%;

4. It has more than 500 customers and an annual revenue run rate of more than US$1 million (approximately RMB 7.28 million);

5. Its intelligent data warehouse product Databricks SQL's revenue run rate has reached US$600 million (approximately RMB 4.4 billion), a year-on-year increase of more than 150%.

In short, Databricks is a platform dedicated to helping companies and organizations manage and analyze data more efficiently. It can not only extract valuable information from massive data, but also support the implementation of AI and machine learning applications through the platform.

▲Databricks product line (Source: SACAR)

Due to the unprecedented craze of artificial intelligence, Databricks has experienced rapid growth in recent quarters. In order to continue to meet growing market demand, the company plans to use the financing funds to develop new AI products, conduct strategic acquisitions, and significantly expand international markets.

01. AI revenue will grow by 300% in 2024, Databricks leads the worldData Intelligence

The founding team of Databricks consists of seven professors and data scientists from the University of California, Berkeley. After 11 years of deep cultivation in the field of cloud computing, Databricks has grown into one of the most valuable private companies in the world.

▲The seven founders of Databricks (Source: Forbes)

Since its establishment, Databricks has quickly attracted strong investment support. The first round of financing was provided by a16z co-founder Ben Horowitz, amounting to US$14 million.

Since then, the company has attracted the attention of about 80 investors, and has raised a total of US$8.6 billion (approximately RMB 62.6 billion) so far. Investors include Thrive Capital, Andreessen Horowitz, DST Global, GIC , Insight Partners and other world-renowned institutions.

Databricks did not disclose new information about the IPO, but co-founder and CEO Ali Ghodsi said at the Cerebral Valley AI Summit in November that if it considers going public, it may take place as early as the middle of next year. .

As a pioneer in the data lake warehouse (Lakehouse) architecture, Databricks innovatively integrates the structured data storage function of the data warehouse with the unstructured and semi-structured data storage capabilities of the data lake, greatly improving Data processing efficiency and reliability.

The company has also launched technologies such as Delta Lake to help users process various types of data on a single platform and conduct deeper analysis.

According to The Information, after OpenAI launched ChatGPT in 2022 and triggered a global AI craze, Ghodsi saw the huge potential of AI in the field of data analysis and decided to increase investment in AI technology.

With the rapid development of AI and machine learning, innovation at the data infrastructure level has become an important driving force for the revenue growth of companies such as Databricks and Snowflake.

▲Databricks co-founder and CEO Ali Ghodsi (Source: The Information)

In 2022, in the face of rising interest rates and economic recession, many technology companies will resort to layoffs and downsizing spending measures, but Ali Ghodsi has chosen a different strategy to focus on company growth. Databricks has fueled its expansion with aggressive sales and engineering hires, nearly doubling the size of its workforce, and multiple acquisitions.

In 2023, Databricks acquired the company for US$1.3 billion (approximately RMB 9.5 billion)AI startup MosaicML. This move helped Databricks release the open source generative AI model DBRX in March 2024, but the model's market sales performed poorly.

In December 2024, Databricks announced that it would cooperate with Meta to introduce the Llama 3.3 70B model to support customers in building enterprise AI agents using Mosaic AI and Llama 3.3.

Ali Ghodsi said that as of November 2024, Mosaic’s revenue (now including all Databricks generative AI products) has increased by 300% year-on-year, marking that Databricks’ investment in the AI ​​business is gradually bearing fruit.

To date, more than 10,000 organizations around the world, including Block, Comcast, Condé Nast, Rivian, Shell (Shell), etc., as well as more than 60% of Fortune 500 companies, are using Databricks’ data intelligence Platform to manage data and use it with AI.

02.Databricks and Snowflake duel Microsoft and Google to accelerate layout

With the advancement of the AI ​​wave, data infrastructure companies are entering an era of increasing competition A fierce new era. Companies such as AWS, Google, Oracle, Microsoft, Databricks and Snowflake have emerged as major players in this space, with both cooperation and fierce competition, and the market landscape is changing rapidly.

Databricks and Snowflake are currently the two major competitors in the field of unified cloud-native data platforms. Although the two companies were founded just a year apart, their products initially were complementary. As Databricks improves query performance and Snowflake gradually adds AI functions, competition between the two gradually intensifies.

Databricks’ core product Delta Lake is an enhanced data lake that supports transactional storage layers and can be deeply integrated with cloud platforms such as AWS, Azure, and Google Cloud. Snowflake positions itself as a modern SQL data warehouse solution that handles structured data and provides powerful data sharing capabilities.

The differences in product positioning between the two companies make their competition not only limited to the competition for market share, but also involves different choices for future technology directions.

▲Snowflake and Databricks product roadmap (Source: IBA GROUP)

Since its listing in 2020, Snowflake’s market value has climbed to US$56.9 billion (approximately RMB 414.5 billion) ), with revenue expected to exceed US$3.4 billion in 2024 (approximately RMB24.8 billion yuan). Although Databricks has not yet gone public, it has become a strong competitor to Snowflake with its early layout in the field of generative AI and its rapidly growing AI business.

▲Snowflake stock price and market value (Source: Futu Niuniu)

In addition to Databricks and Snowflake, large cloud infrastructure companies such as Microsoft, Google, and AWS are also accelerating their layout related to AI data products, further intensifying market competition.

Google’s BigQuery has strong advantages in data analysis and AI computing, becoming the main challenger to Databricks and Snowflake; Amazon AWS continues to seize the AI ​​market with its mature cloud computing infrastructure, combined with AI services such as SageMaker Data processing market share; Microsoft has strengthened its penetration into the data infrastructure market by launching the Fabric data platform, becoming a major threat to Databricks.

In this competitive landscape, Oracle is not to be outdone and quickly accelerates its entry into the generative AI market, launching the OCI Generative AI service to provide enterprise customers with tools to build AI models. In September 2023, Oracle's database services were integrated into Microsoft Azure to provide Microsoft customers with more complete AI data infrastructure solutions.

Although Databricks has always had a close relationship with Microsoft. Databricks once relied on Microsoft's Azure platform to provide cloud computing infrastructure. However, with the launch of Microsoft's Fabric platform, Databricks began to reduce its reliance on Microsoft and instead strengthened its cooperation with Google Cloud. Cooperation with AWS.

Five years ago, about 50% of Databricks' revenue came from the Microsoft Azure platform. Today, Databricks' revenue sources have tended to be diversified, with revenue from Microsoft and AWS roughly equal.

03. Conclusion: When will investors’ crazy bets on Databricks’ money-burning end?

Databricks has attracted top investors around the world with its powerful technology and growing demand for AI. The total amount of financing in this round has exceeded 86 billion dollars. However, the company's expansion has been accompanied by huge expenditures on R&D and acquisitions. Although its AI strategy is gradually bearing fruit, it still has not achieved positive free cash flow.

With intensifying competition and economic uncertainty, whether Databricks can maintain high growth and find a sustainable profit model remains a key question. The current cash burning model has promoted the company's development, and how to achieve profitability in the future will be the focus of investors.

Can Databricks survive the intenseStanding out from the competition and eventually turning it into a stable source of profit determines whether it can continue to lead the global data intelligence market.