Also read: Databricks, champion of data “lakehouse” model, closes $1B series G funding round
On golden lake
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. In addition, the pure data lake and ML capabilities deriving from technologies like Apache Spark, Delta Lake and MLflow mean that data scientists, data engineers and software engineers, each using their preferred programming languages, can have direct file access to the lake, benefitting from its open architecture.
Don’t spend it all in one place
Beyond R&D, the company, in its press release, said the money raised will go toward “entering new markets, enabling and growing its partner ecosystem, and building a broad catalog of industry solutions.” In addition, the company will need to invest in its go to market strategy to make the lakehouse concept more mainstream. With that in mind, Databricks is also announcing the hiring of Andrew Kofoid as President of Global Field Operations. Kofoid comes to Databricks from Salesforce where he was President, North America and responsible for $10 billion revenue annually, according to Ghodsi.
Game on
With all this mojo behind the lakehouse concept, it’s time for data warehouse players, like Snowflake, AWS, Vertica/Micro Focus, Yellowbrick and others to return serve. While lakehouse proponents may say the warehouse is obsolete, most cloud data warehouse players believe they’ve eliminated the justification to use a separate data lake in the first place. Now, having raised its eighth major funding round, Databricks will keep the rivalry in play, and in the spotlight.
