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Databricks Funding History
Databricks is a US data and AI company operating the Databricks Data Intelligence Platform for lakehouse analytics, data engineering and AI workloads.
Company Overview
Founded 2013 · San Francisco, California, US
Official WebsiteDatabricks Funding Timeline
Strategic
$5B · $190B valuation
Databricks said the funding would support its Lakebase database, Genie assistant and Unity AI Gateway.
Led by Coatue. Participation included Blackstone, MGX, T. Rowe Price, Sixth Street Growth.
Source · databricks.com ↗Series L
over US$4 billion
Databricks said the Series L would support its Lakebase database and Agent Bricks platform.
Led by Insight Partners, Fidelity Investments. Participation included Andreessen Horowitz, BlackRock, Blackstone, Coatue, GIC, MGX, NEA, Ontario Teachers' Pension Plan, T. Rowe Price, Temasek, Thrive Capital.
Source · reuters.com ↗Series K
~US$1 billion (medium confidence)
Databricks said it would expand Agent Bricks, bring its Lakebase database to market, and support international growth. Databricks said the Series K valued it at more than $100 billion.
Led by Andreessen Horowitz, Insight Partners, MGX, Thrive Capital.
Source · databricks.com ↗Series J Close + Debt
US$15.3B total financing incl. US$5.25B debt
The transaction closed the previously announced Series J equity round and added a separate debt facility.
Source · techcrunch.com ↗Series J
US$10 billion
Databricks said the financing would help fund new AI products, international expansion and liquidity for employees.
Led by Thrive Capital.
Source · databricks.com ↗Series I
US$500 million (I + top-up)
NVIDIA joined as a new investor in the initial Series I, and Databricks announced additional strategic investors at later closings.
Led by T. Rowe Price. Participation included Andreessen Horowitz, Counterpoint Global, Fidelity Investments, Franklin Templeton, GIC, Tiger Global, Ontario Teachers' Pension Plan, NVIDIA.
Source · prnewswire.com ↗Series H
US$1.6 billion
Databricks said the proceeds would expand adoption of its lakehouse architecture across public clouds and support entry into new markets.
Led by Counterpoint Global.
Source · databricks.com ↗Series G
US$1 billion · $28B valuation
Databricks said it would expand globally and develop more capabilities for its data platform as adoption grew.
Led by Franklin Templeton.
Source · databricks.com ↗Series F
US$400 million
Databricks raised the round as it expanded its analytics platform, which included Delta Lake for data storage and MLflow for managing machine learning experiments.
Led by Andreessen Horowitz. Participation included BlackRock, T. Rowe Price, Tiger Global, Alkeon Capital, Coatue, Dragoneer Investment Group, Geodesic Capital, Microsoft, NEA.
Source · globalventuring.com ↗Series E
US$250 million
Databricks planned to expand its unified analytics platform and support demand for analytics and machine learning on Apache Spark.
Participation included Andreessen Horowitz.
Source · en.wikipedia.org ↗Series D
$140 million
Databricks said it would expand its Unified Analytics Platform and bring it to more markets. The platform was built on Apache Spark.
Led by Andreessen Horowitz. Participation included NEA, Battery Ventures.
Source · databricks.com ↗Series C
$60 million
Databricks planned to deepen its work on Apache Spark and invest in its commercial data platform.
Led by NEA. Participation included Andreessen Horowitz.
Source · databricks.com ↗Series B Funding
$33 million
Databricks announced the close alongside the launch of its cloud analytics platform built on Apache Spark.
Led by NEA. Participation included Andreessen Horowitz.
Source · databricks.com ↗
Databricks Founding Team
Seven researchers from UC Berkeley’s AMP Lab founded Databricks in 2013: Ali Ghodsi, Andy Konwinski, Arsalan Tavakoli-Shiraji, Ion Stoica, Matei Zaharia, Patrick Wendell, and Reynold Xin. Their work grew out of open-source data processing research, including Apache Spark.
Databricks Products
Databricks Company Development
A Data Platform Expanded into AI Workloads
Databricks built around lakehouse analytics and data engineering, then made AI workloads part of the same platform. That gives teams a route to use the data they already prepare for analytics in model development and deployment.
Databricks Competitive Landscape
Data Architecture Underneath the AI Tools
Databricks and Snowflake both serve enterprise analytics and AI teams. A meaningful comparison begins with how each platform manages storage, compute and data access across existing pipelines before considering the model tools built on top.
