Last week, Databricks raised $400 million in a Series F funding round, bringing the company's total funding to almost $1 billion (making Databricks an almost-minotaur).
Databricks has built a platform that helps its customers unify their analytics across business, data science, and data engineering on top of an open-source framework.
Its product suite consists of:
- Delta Lake, an open-source data lake product
- MLflow, an open-source project that helps data teams operationalize machine learning
- Koalas, which creates a single machine framework for Spark and Pandos
- Spark, the open-source analytics engine
With machine learning optimization tools, businesses can take machine learning models and algorithms built by data scientists and machine learning developers and put them into action. Check out machine learning operationalization software on G2. |
With a $200 million run rate, Databricks seems to have found the sweet spot in terms of how to monetize a value-add platform built on top of open-source technology. If you thought that there is no money in open source, this might make you think twice (also, see IBM’s 2019 acquisition of open-source software provider Red Hat for $34 billion).
According to CEO Ali Ghosdi, the new funding will primarily be used for research and development. In addition, over the next three years, the company is looking to invest €100 million into its new European data center in Amsterdam.
“Our bets on massive data processing, machine learning, open source and the shift to the cloud are all playing out in the market and resulting in enormous and rapidly growing global customer demand,” Ali said in a statement.