According to reports from Zhitong Finance APP, Databricks Inc., known as a 'super unicorn', is raising 10 billion dollars in new funding. This substantial cash injection will immediately elevate the valuation of this next-generation software company focused on data analytics and AI, which is greatly benefiting from the unprecedented wave of global enterprises laying out AI, to an astonishing 62 billion dollars, highlighting the influx of global capital into software companies under the AI wave, especially those focused on Big Data and AI. Databricks is committed to providing enterprises with a one-stop efficient solution in data engineering, data science, machine learning, and AI large model fields through its cloud platform ecosystem.

Statistics compiled by institutions show that this startup software company is now one of the highest-valued private companies in the world. A statement released by Databricks on Tuesday indicated: 'The company intends to use this funding for new AI suite products, acquisitions, and significant expansion in international market operations.' Additionally, this funding will also be used to purchase a portion of shares held by current and former employees.

It is understood that the lead investor in this round of Databricks financing is the venture capital giant Thrive Capital, with participation from other venture capital firms including Andreessen Horowitz and DST Global. 'These guys are execution machines. They are ready to become a public company,' said Vince Hankes, a partner at Thrive Capital, in an interview with the media. 'Raising a significant amount of funds and providing liquidity for employees can alleviate the pressures faced by startups.'

Earnings Reports data shows that for the fiscal year ending January 2025, Databricks expects its annual benchmark revenue to exceed 3 billion dollars. In the most recent statistical quarter ending in October, Databricks' total revenue growth rate exceeded 60%, representing a very rapid expansion rate compared to traditional software companies that are struggling to achieve performance growth.

Databricks rides the wave of AI alongside Snowflake, but its valuation has already surged far ahead.

Databricks' latest valuation of up to 620 dollars means that this startup's valuation has surpassed that of its long-standing 'strong competitor' in data platforms and Big Data analytics—namely the US-listed company Snowflake (SNOW.US), which had a total market capitalization of approximately 56.3 billion dollars as of Tuesday's market close.

Databricks, as a data and AI platform company, focuses its core competitiveness on Big Data processing (based on Apache Spark), data science, machine learning, and AI, dedicated to providing an integrated and efficient workflow for corporate data analysis departments, data scientists, data engineers, and corporate machine learning teams. Snowflake is one of Databricks' main competitors. Although their products and services differ, there is a substantial overlap in their target markets. Both provide cloud-based data platforms that help enterprises manage Data Storage, Data Processing and Analysis, and machine learning workflows.

In contrast to Snowflake, Databricks Lakehouse emphasizes the combination of the advantages of data lakes and data warehouses, merging the complex data structures originally difficult to handle within data lakes with efficient query and analysis capabilities, supporting ACID transactions and stream processing functionalities. Snowflake focuses more on achieving seamless integration of data lakes and data warehouses on a single platform, supporting structured and semi-structured data storage while providing efficient query capabilities, but its architecture does not particularly emphasize transaction support and stream processing, focusing more on efficient batch processing and analysis.

Databricks' valuation has surpassed Snowflake — the latest round of financing values Databricks at 62 billion dollars.

Snowflake focuses on cloud data warehousing, aiming to provide a high-performance, distributed data storage and querying platform, particularly excelling in the storage, querying, and analysis of structured and semi-structured data, while also offering powerful data sharing and multi-cloud support. Databricks similarly focuses on Data Storage as well as Data Processing and Analysis, but with the generative AI wave led by ChatGPT sweeping the globe, these two software companies focusing on data platforms are shifting their business focus toward new generative AI products that connect the data platform ecosystem, which is also the core logic behind Snowflake's strong quarterly performance and recent sharp rise in stock price.

Databricks provides a highly integrated cloud platform that not only helps enterprises efficiently invoke Databricks' data processing and analysis modules in a generative AI chatbox manner, providing non-IT professionals with an efficient and convenient operational path, but also supports the development, training, and deployment of generative AI large models (such as OpenAI GPT, Transformer models, etc.). Through integration with OpenAI and MLflow, Databricks helps businesses implement generative AI applications, simplifying the workflow of data science, model training, and deployment.

Snowflake provides multiple convenient data solutions based on generative AI, including data storage, processing, and Big Data analysis, helping users directly use ready-made AI models and services within its platform. These services include text generation, NLP analysis, image generation, among others, and have already been integrated with Snowflake's cloud data warehouse, allowing enterprises to quickly access the platform ecosystem within the Snowflake cloud platform, streamlining the workflow of data science and analysis.

In the wave of AI, the valuations of new-generation software entities such as Databricks are expected to continue expanding.

Databricks CEO Ali Ghodsi stated in a media interview that maintaining this incredible growth rate means expanding Databricks' market promotion and talent in AI engineering. As for potential acquisitions, Ghodsi mentioned that he is looking for startups focused on AI applications to acquire key technologies and talent.

Ghodsi emphasized in the interview: "There are many very smart people out there with great ideas, but perhaps their monetization plans haven't gone as expected, and we might be able to help."

Databricks focuses on developing data processing Software and has recently shifted its business focus to processing, extracting, and analyzing extremely complex data from various sources to build AI-based applications. Its main competitors are generally considered to be Snowflake and similar services provided by some cloud infrastructure vendors (such as Fabric under the USA technology giant Microsoft).

Some institutional investors and hedge funds have been waiting for the software leader Databricks to go public (i.e., IPO), but the company’s strong ability to continuously raise large amounts of capital from the private market allows it to continually postpone its schedule for listing on the US stock market, and the valuation may continue to expand significantly before the IPO, ultimately benefiting greatly from the AI wave, making it very likely that Databricks' valuation will exceed 100 billion dollars before going public.

"Theoretically, we would go public as early as next year," Ghodsi said. "This gives us some flexibility in providing liquidity opportunities for employees."

It is understood that in the latest round of financing, other supporters included Singapore's sovereign wealth fund GIC Pte Ltd, as well as Insight Partners and WCM Investment Management. According to informed sources, Lightspeed Venture Partners also participated in the deal. One source said that the company invested 0.2 billion dollars in this round of financing, and since the discussion is about private information, the person requested anonymity. Representatives from Lightspeed and Databricks declined to comment on the details of this round of financing.

The company stated that its direct competitor Snowflake's data warehouse product, Databricks SQL, has reached 0.6 billion dollars in revenue with a year-over-year growth rate exceeding 150%. The company also stated that over 500 customers spend more than 1 million dollars annually on the Databricks data warehouse platform.

This funding will also help cover the taxes related to employee stock sales. Last week, Bloomberg reported that Databricks is seeking about 2.5 billion dollars in debt from private credit institutions to help offset the associated tax burden.

Thrive has participated in other large employee equity buyout offers or significant transactions that allow employees to sell their shares, including the strongest unicorn in the AI field, OpenAI, which is valued at up to 159 billion USD, and the payment unicorn, Stripe.

"This has become an expectation for employees, as the alternative is to go to Google or Meta for highly liquid stocks," said Hanks from Thrive. "These are indeed very unique situations that allow these startups to compete with large tech companies."

According to CB Insights, Databricks' latest valuation has expanded significantly from around 50 billion USD in November to 62 billion USD, second only to a few non-public private companies like OpenAI and SpaceX.

Looking ahead, analysts generally expect Databricks, as well as software companies like the "strongest AI unicorn" OpenAI, to continue to see expansion in valuation. Analysts anticipate that software companies will have stronger revenue data as a core pillar for valuation amid the epic AI boom, and these companies are expected to continue leading the AI investment wave, which is also the core logic behind the recent surge in stock prices of software giants like Snowflake, Amazon, Salesforce, ServiceNow, Palantir, and AppLovin.

A research report released by international banking giant ubs group shows that the global technology industry has just begun a large-scale performance growth cycle. ubs expects that by 2027, ai technology will achieve extremely widespread application in various industries across major economies, thereby pushing the ai large models and ai software applications to become a segmented market valued at 225 billion dollars, a massive leap compared to only 2.2 billion dollars in 2022, with a compound annual growth rate expected to reach 152%. ubs also predicts that the total revenue scale of the ai industry will increase 15-fold, rising from approximately 28 billion dollars in 2022 to 420 billion dollars in 2027.