They grapple with data silos that prevent a single source of truth, the expense of maintaining complicated data pipelines, and reduced decision-making speed. The answer to this complexity is the lakehouse, a platform architecture that implements similar data structures and data management features to those in a data warehouse directly on the low-cost, flexible storage used for cloud data lakes. This new, simplified architecture allows traditional analytics and data science to co-exist in the same system. To bring this to life, Databricks recently announced the new SQL Analytics service to provide customers with a first-class experience for performing BI and SQL workloads directly on the data lake, augmenting the rich data science and data engineering capabilities already available in the Databricks platform. With this launch, we are the first to realize the complete vision of lakehouse architecture to deliver 9x better price/performance than traditional cloud data warehouses.
Databricks, the Data and AI company and pioneer of the data lakehouse architecture, today announced Databricks Partner Connect, a one-stop portal for customers to quickly discover a broad set of validated data, analytics, and AI tools and easily integrate them with their Databricks lakehouse across multiple cloud providers. Integrations with Databricks partners Fivetran, Labelbox, Microsoft Power BI, Prophecy, Rivery, and Tableau are initially available to customers, with Airbyte, Blitzz, dbt Labs, and many more to come in the months ahead. Enterprises want to drive complexity out of their data infrastructure and adopt more open technologies to take better advantage of analytics and AI. The data lakehouse enabled by Databricks has put thousands of customers on this path, collectively processing multiple exabytes of data a day on a single platform for analytics and AI workloads. But, the data ecosystem is vast, and no one vendor can accomplish everything.
What better way to ensure you have a growing pipeline of customers than to invest them? Databricks hasn't even gone public yet, but the San Francisco decacorn recently announced a new investment division, Databricks Ventures, to support other startups that are building on its ecosystem. The eight-year-old San Francisco company hasn't raised a specific amount for the fund but will draw from its own balance sheet when it decides to invest. It won't lead any funding rounds, either, but will participate when it makes strategic sense to do so, Andrew Ferguson, who oversees the new venture arm at Databricks, told me. And if that vision is aligned with Databricks and our customer base, that's really where we can partner with them to help accelerate their business, and then it's also good for Databricks as well as being a good financial investment.
January was a huge month for data lake-focused companies' funding. Now that we've ticked over into February, it looks like the data "lakehouse" is getting its due as well. Databricks, the company founded by the creators of Apache Spark, and focused on machine learning, streaming data processing, data lake and SQL analytics, has just closed a whopping $1 billion (yup, with a "b") series G funding round, putting the company at a $28 billion post-money valuation. The collective of investors is impressive and unusual: Franklin Templeton leads the round and is joined by Canada Pension Plan Investment Board, Fidelity Management & Research LLC and Whale Rock, along with new strategic investors Amazon Web Services, Alphabet's CapitalG and Salesforce Ventures. Also participating are a slew of existing investors: Microsoft, Andreessen Horowitz, Alkeon Capital Management, BlackRock, Coatue Management, T. Rowe Price Associates, Inc. and Tiger Global Management.
Databricks has done it again. This morning the company is announcing it has closed on a $1.6 billion funding round, led by Counterpoint Global (Morgan Stanley). Other new investors include BNY Mellon, Clearbridge and the University of California Endowment; most existing investors participated as well. This round follows a $1 billion series G round in February of this year, brings total funding to almost $3.5 billion and post-money valuation to $38 billion. Also read: Databricks, champion of data "lakehouse" model, closes $1B series G funding round ZDNet spoke with Databricks CEO, Ali Ghodsi, who explained the money will fund research and development around the company's data lakehouse concept, which involves uniting the performance characteristics of a data warehouse with the open formats used in data lake storage.