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Databricks

Category: AI Infrastructure

A unified Data and AI platform built on the Lakehouse architecture that integrates data engineering, data science, machine learning, and analytics into a single collaborative environment. Databricks was founded in 2013. The company is led by Ali Ghodsi. Based in San Francisco, United States. Team size: 12,000+. Total funding raised: $9.0B+. Latest round: Series J ($5.0B, Feb 2026). Key investors include Andreessen Horowitz, Thrive Capital, MGX, NVIDIA, Microsoft, Amazon, CapitalG, Morgan Stanley, T. Rowe Price, NEA, Coatue.

AMW Analysis

Databricks operates a unified Data and AI platform built on the Lakehouse architecture, combining data engineering, data science, machine learning, and analytics in one environment, with a stated goal of eliminating data silos through integrated generative AI ("Data Intelligence"). Founded in 2013 and based in San Francisco, the company has raised over $9.0B total, most recently a $5.0B Series J in February 2026 from investors including Andreessen Horowitz, Thrive Capital, MGX, NVIDIA, Microsoft, Amazon, and Coatue, among others.

Recent news flow shows rapid valuation growth, reaching a reported $188B following a Coatue-led investment, alongside active platform expansion: the open-source Omnigent project for multi-agent orchestration, the LTAP architecture unifying transactional and analytical processing on lake storage, and the Lakewatch agentic SIEM product following the Antimatter and SiftD.ai acquisitions, marking an entry into cybersecurity. The company has also expanded internationally, increasing Singapore headcount and committing $300M toward an Australia/New Zealand expansion with a new Sydney office, reporting 85% year-on-year regional growth. Databricks Ventures has also participated in external funding rounds, including a Series B for an agentic web search platform.

AMW analysis, generated from 8 tracked news signals.

Founded
2013
Headquarters
San Francisco, United States
Team size
12,000+
Total funding
$9.0B+

Value proposition

Eliminates data silos by combining the performance and governance of a data warehouse with the flexibility and low cost of a data lake, enabling 'Data Intelligence' through integrated generative AI.

Products and solutions

Databricks SQL (Serverless data warehousing), Delta Lake (Open-source storage layer for reliability), Unity Catalog (Unified governance for data and AI), Mosaic AI (End-to-end platform for building and deploying LLMs), MLflow (Machine learning lifecycle management), Photon (High-performance vectorized query engine), Delta Live Tables (ETL framework)

Unique value

Pioneered the 'Lakehouse' architecture, which effectively merged the previously separate worlds of data lakes and data warehouses into a single platform.

Target customer

Fortune 500 enterprises, data engineering teams, data scientists, ML engineers, and business intelligence analysts.

Industries served

Financial Services, Healthcare & Life Sciences, Retail & Consumer Goods, Manufacturing & Energy, Media & Entertainment, Public Sector

Technology advantage

Built by the original creators of Apache Spark; features a proprietary high-performance engine (Photon) and deep integration with generative AI via the Mosaic AI acquisition, allowing companies to train custom models on private data.

How they differentiate

Pioneered the 'Lakehouse' architecture which unifies data lakes and data warehouses. Unlike competitors that often require separate systems for BI and AI, Databricks provides a single platform for data engineering, machine learning, and analytics, heavily integrated with open-source standards like Apache Spark and Delta Lake.

Main competitors

Snowflake, Google BigQuery, Amazon Redshift, Microsoft Azure Synapse/Fabric

Key partnerships

Microsoft (Azure Databricks is a first-party service on Azure), Amazon Web Services (AWS), Google Cloud Platform (GCP), NVIDIA (Optimizing AI training and inference on Databricks), Accenture & Deloitte (Global strategic implementation partners)

Notable customers

Shell, Comcast, Condé Nast, Regeneron, H&M, AT&T, Walgreens

Major milestones

Pioneered the 'Lakehouse' category in 2020, Acquired MosaicML for $1.3B in 2023 to bolster Generative AI capabilities, Reached $1B+ revenue run rate in 2022, Completed a $5B equity and debt round in Feb 2026 at a $134B valuation, Agreed to acquire Panther (agentic SIEM/security lakehouse) in Jun 2026, its third security acquisition after Antimatter and SiftD.ai, Signed term sheet for a Coatue-led strategic funding round at $188B valuation in Jul 2026

Growth metrics

Achieved a $5.4 billion annual revenue run rate (Feb 2026, +65% YoY); valuation reached $134B in Feb 2026, then $188B by Jul 2026 following a new Coatue-led strategic round.

Market positioning

Dominant leader in the Data Intelligence and AI Infrastructure market for large-scale enterprises.

Geographic focus

Global (Headquartered in North America with significant operations in EMEA, Asia-Pacific, and Latin America).

Patents and IP

Holds numerous patents in distributed systems, optimized data storage formats (Delta), and automated query optimization for cloud-native environments.

About Ali Ghodsi

Ali Ghodsi is the Co-founder and CEO of Databricks and a central figure in the modern data ecosystem. He is one of the original creators of Apache Spark, Delta Lake, and MLflow. Before becoming CEO in 2016, he served as the company's VP of Engineering and Product Management. He is an Adjunct Professor at UC Berkeley and was a key researcher at the AMPLab, where he co-authored the seminal papers on Mesos and Spark. Under his leadership, Databricks pioneered the 'Lakehouse' architecture, merging data warehouses and data lakes.

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