SAN FRANCISCO – September 9, 2021 – Databricks, the Data and AI company and a pioneer of the data lakehouse architecture, today announced the final closing of their recent Series H funding. Cloud leaders and existing investors Amazon Web Services (AWS), CapitalG, and Microsoft will participate in Databricks’ $1.6 billion round of funding, which puts the company at a $38 billion post-money valuation. The Series H funding will be used to accelerate innovation and adoption of the lakehouse as the data architecture’s popularity across data-driven organizations continues to grow at a rapid pace.
“We are delighted to once again include our most strategic partners in this latest round of funding, as it validates our vision for an open and unified approach to data and AI on any cloud,” said Ali Ghodsi, Co-Founder and CEO of Databricks. “As we jointly make more organizations successful in their move to the cloud and accelerate adoption of the lakehouse architecture, we’re excited to see these partnerships – and the ecosystems formed around them – continue to grow for decades to come.”
Databricks has pioneered a simple and open architecture for data and AI, which brings the reliability, governance, and performance of a data warehouse directly to the data lakes that most organizations already store all of their data in. Rather than being forced to move data out of the data lake, and between various disconnected and legacy systems for different use cases, Databricks customers are building analytics platforms on AWS, Microsoft Azure, and Google Cloud to support every data and analytics workload in a single, unified location.
Databricks is the data and AI company. More than 5,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.