Databricks Startup Profile

THE CODEW · STARTUP PROFILE

Databricks

Data and AI platform company built on the lakehouse architecture — unifying data engineering, analytics, governance, and AI for enterprises

Primary Category: Artificial Intelligence and AI Infrastructure · Status: Private · Last Verified: November 2026

1. Company Overview

• Company name: Databricks, Inc.
• Official website: databricks.com
• Founding year: 2013
• Headquarters: San Francisco, California, United States
• Current operating status: Private. One of the largest and highest-valued private software companies; continues to raise growth capital rather than pursue a near-term IPO as of late 2026 statements.
• One-sentence description: Databricks provides a unified cloud platform for data storage, processing, governance, analytics, and AI — centered on the open lakehouse architecture — so organizations can build data and AI applications on their own data.

2. What the Startup Does

• Core problem: Enterprises struggle with fragmented data systems (data lakes, warehouses, operational databases, and AI tooling). Moving data between systems creates complexity, cost, and governance risk, while AI applications need reliable access to governed business data.
• Product / service: A Data + AI Platform that combines lakehouse storage and compute, data warehousing, governance (Unity Catalog), operational databases (Lakebase), AI agent tooling (Agent Bricks and related), and conversational analytics (Genie), running on major public clouds.
• Target customers: Large enterprises and organizations across industries that need to manage large-scale data and build AI applications. Reported customer base includes a substantial share of the Fortune 500 and more than 20,000 organizations.
• Value proposition: One platform for data engineering, analytics, governance, and AI — reducing the need to stitch together separate systems and enabling AI agents and applications to run on governed enterprise data.

3. Technology and Products

• Main products and platforms:
  • Lakehouse platform (storage, compute, and analytics grounded in open formats and Delta Lake)
  • Unity Catalog — data and AI governance
  • Lakebase — operational / OLTP database capabilities designed for AI agents
  • Agent Bricks and related AI agent development tools
  • Genie — conversational interface for querying and analyzing data
  • Lakeflow, Lakewatch, Databricks Apps, and other platform components
  • MLflow and other open-source projects historically associated with the company
• Technical approach: Open lakehouse architecture that unifies data lake and warehouse capabilities. Heavy investment in open-source foundations (Apache Spark, Delta Lake, MLflow, Unity Catalog) and cloud-native multi-cloud deployment (AWS, Azure, Google Cloud).
• Focus tags: Artificial Intelligence and AI Infrastructure (primary); Enterprise Software and SaaS; Data Platforms
• Product availability and maturity: Mature core platform used by thousands of enterprises; rapid expansion into AI agents, operational databases, and application-layer products.

4. Founders and Leadership

• Ali Ghodsi — Co-founder & Chief Executive Officer. Founder Profile to be published.
• Ion Stoica — Co-founder & Executive Chairman (former CEO).
• Matei Zaharia — Co-founder & Chief Technology Officer (creator of Apache Spark).
• Reynold Xin — Co-founder & Chief Architect.
• Patrick Wendell — Co-founder (engineering leadership).
• Andy Konwinski — Co-founder.
• Arsalan Tavakoli-Shiraji — Co-founder (field engineering / go-to-market leadership).

The founding team originated from UC Berkeley research that produced Apache Spark and related open-source systems. Individual Founder Profiles will be linked as they are published, beginning with Ali Ghodsi.

5. Business Model

• Model type: Consumption-based / usage-based cloud software. Customers pay primarily for compute and platform usage rather than traditional seat licenses.
• Target customer segments: Large enterprises and data-intensive organizations across industries; expanding AI and agent workloads alongside classic data engineering and analytics.
• Distribution and go-to-market: Enterprise sales, cloud marketplace partnerships (AWS, Azure, Google Cloud), and product-led expansion within existing accounts. High net retention reported in public company commentary.

6. Funding and Investors

Only verified or strongly corroborated figures are shown. Historical rounds are preserved. Later reported activity is labeled accordingly.

• Current stage: Late-stage private.
• Latest major announced round: August 2026 — approximately $5 billion strategic / later-stage round at a $190 billion post-money valuation. Participants reported to include Coatue, Blackstone, MGX, T. Rowe Price, and others.
• Prior major rounds (selected):
  • December 2025 — Series L: more than $4 billion at approximately $134 billion valuation
  • 2024–2025 — large growth rounds including a reported $10 billion round at $62 billion (December 2024) and subsequent step-ups
  • Earlier rounds dating to 2013 with foundational backers including Andreessen Horowitz and NEA
• Total capital context: Equity raised reported in the mid-to-high teens to low twenties of billions of dollars range across sources, with additional debt facilities. Exact totals vary by inclusion of debt and secondary activity.
• Notable investors: Andreessen Horowitz, NEA, Insight Partners, Coatue, Thrive Capital, Fidelity, Microsoft, and a broad set of growth and institutional investors.
• Revenue markers (company-reported / widely cited): Revenue run-rate figures publicly associated with the company have included levels above $5 billion (early 2026) and above $7 billion (mid-to-late 2026), with strong year-over-year growth rates cited in the 65–80%+ range. Treat as company-reported run-rate figures rather than audited GAAP revenue.
• Links to Term Sheet coverage will be added as articles are published.

7. Market and Competition

• Primary industry / sub-industry: Data platforms and enterprise AI infrastructure.
• Competitors and alternatives: Snowflake (closest public peer in data platforms), cloud-native offerings from AWS, Microsoft Azure, and Google Cloud, traditional data warehouse and analytics vendors, and specialized AI infrastructure providers.
• Differentiation: Open lakehouse architecture; strong open-source heritage (Spark, Delta Lake, MLflow); unified data + AI positioning; multi-cloud footprint; rapid expansion into AI agents and operational databases on the same governed data foundation.
• Relevant market developments: Enterprise demand for AI agents that operate on internal data; convergence of data platforms and AI application infrastructure; ongoing competition with Snowflake and hyperscalers.

8. Growth and Milestones

• 2013 — Founded by UC Berkeley researchers who created Apache Spark and related systems.
• Evolution from managed Spark offering to the full lakehouse platform (Delta Lake, Unity Catalog, and broader data + AI suite).
• Major product expansions into governance, AI agents (Agent Bricks), conversational analytics (Genie), and operational databases (Lakebase).
• 2024–2026 — Series of large growth and strategic rounds culminating in the August 2026 raise at approximately $190 billion valuation; revenue run-rate reported above $7 billion.
• Continued customer expansion (reported >20,000 organizations and high Fortune 500 penetration) and free-cash-flow positive commentary in recent periods.

9. The CODEW Coverage

• Startup Spotlight — to be linked when published
• The Term Sheet — funding and valuation coverage
• Company Analysis / Deep Dive — to be added when published
• AI Infrastructure and Data Platform Watch coverage

This profile is the reference record. Editorial features link back here.

10. Sources and Last Verified

• Databricks official website and public product / company announcements
• Contemporaneous reporting on funding rounds (including the August 2026 $5B / ~$190B round) from multiple independent outlets
• Founding team and open-source heritage details corroborated across independent sources

Verification labels: Confirmed / Corroborated for founding, core platform direction, leadership roles, and announced major funding rounds through August 2026. Revenue run-rate and secondary valuation marks are presented as reported.
Last verified: November 2026.

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