- Specialization
Data Engineeringand 1 more specialization valuesLess
- Distributed Computing
- Business
- Software Applications
- Market
- Cross Industry
- Ecosystem
- Not classified
- Customers
Enterprisesand 1 more customers valuesLess
- Developers
More details
- Organization type
- Commercial Company
- Ecosystem
- Not classified
- Business
- Software Applications
- Specialization
- Data Engineering, Distributed Computing
- Market
- Cross Industry
- Customers
- Enterprises, Developers
- Delivery models
- Hosted Software
- Revenue models
- Usage Based
- Listing status
- Not classified
- Latest equity round
- Not classified
- Reported funding amount
- $1B+
About
Databricks builds the Data Intelligence Platform, an open-lakehouse foundation that unifies data, governance, analytics, and AI. It sells to organizations ranging from large enterprises to Fortune 500 companies, differentiating itself through its unified architecture and origins in Apache Spark, Delta Lake, MLflow, and Unity Catalog.
Market
Databricks competes in the enterprise data, analytics, machine learning, and generative-AI platform market. It positions its open Lakehouse architecture as a unified foundation that combines data lakes and warehouses, while differentiating through integrated governance, cross-cloud data and AI asset management, open-source technologies such as Spark and Delta Lake, and built-in AI capabilities.
Large enterprises and data-intensive organizations across industries, particularly those seeking to unify data engineering, analytics, machine learning, governance, and generative AI. Primary buyers and users are likely CIOs/CDOs, data and analytics leaders, data engineers, ML teams, and governance stakeholders; Databricks reports more than 20,000 organizational customers and adoption by 70% of the Fortune 500.
At a Glance
Problem
Organizations often struggle with the complexity of turning data into governed analytics and useful AI. Data engineering, warehousing, machine learning, governance, and application development can become disconnected activities, making it harder for business users to access reliable information and for technical teams to scale AI securely. Databricks addresses this pain by simplifying and democratizing data and AI, reducing the friction and delay between raw data, insight, and production use.
The main use case is a governed, end-to-end data-to-AI workflow: prepare enterprise data, run analytics or real-time pipelines, build machine-learning or large-language models, and deploy the resulting intelligence in secure applications and products. The economic value is primarily operational—less platform complexity and faster movement from data to decisions, automation, and AI-enabled products—rather than a single narrowly defined application.
Product / Service
Databricks provides a cloud-delivered Data Intelligence Platform built on an open lakehouse architecture. It combines a unified foundation for data and governance with AI models tuned to an organization’s specific characteristics, and covers ETL, data warehousing, advanced analytics, machine learning, generative AI, MLOps, model serving, streaming, and data applications. The platform operates across major cloud environments, allowing organizations to use a common data and AI approach without maintaining entirely separate systems for each workload.
The benefit is an integrated workflow for both technical and nontechnical users. Automation and natural-language capabilities help people discover and use data, while engineering and data teams can build and deploy governed, secure data and AI applications. By bringing preparation, analysis, modeling, governance, and deployment together, Databricks aims to accelerate data and AI initiatives while preserving security and control.
Market
Databricks competes in the enterprise data and AI platform market, spanning lakehouse infrastructure, data engineering, cloud data warehousing, advanced analytics, machine learning, generative AI, and data applications. Its competitive set includes Snowflake, Google BigQuery, Amazon Redshift, Apache Spark, Dremio, and other open-source and cloud-native tools competing for overlapping data and AI workloads. Databricks’ positioning is the integration of an open lakehouse, governance, analytics, and AI development in one platform.
The company has substantial commercial traction and is not pre-revenue based on the evidence of broad customer adoption. Databricks reports that more than 20,000 organizations worldwide use its platform, including Block, Comcast, Condé Nast, Rivian, and Shell, and that 70% of the Fortune 500 rely on it. This indicates meaningful enterprise penetration, although the cited material emphasizes customer count and adoption rather than providing an audited revenue figure.
Founders & Leadership
Funding History
Andreessen Horowitz
New Enterprise Associates
New Enterprise Associates
Andreessen Horowitz
Andreessen Horowitz
Andreessen Horowitz
Franklin Templeton Investments
Morgan Stanley
T. Rowe Price
Nvidia, Capital One, Andreessen Horowitz, Fidelity Investments, Insight Partners, Tiger Global Management, Thrive Capital
Not disclosed
Andreessen Horowitz, Insight Partners, MGX, Thrive Capital, WCM Investment Management
Insight Partners, Fidelity Investments, J.P. Morgan
Not disclosed
Coatue Management
Recent News
Databricks and Cal Athletics announced a multi-year partnership that names Cal’s football venue Databricks Field at California Memorial Stadium. The agreement also makes Databricks the official Enterprise Data + AI platform for Cal Athletics and includes other stadium and team branding rights.
Helix and Databricks announced a partnership to launch Helix Research Workspaces, a trusted research environment for population-scale clinicogenomic research. The environment gives approved research partners governed access to compute, storage, and analysis tools for more than 550,000 clinicogenomic records.
Databricks announced it had acquired Row Zero, a spreadsheet built for people and AI agents to work with data. Databricks said the acquisition would add a spreadsheet interface for exploring, modeling, and collaborating on governed data in its Genie AI coworker.
Intelo.ai announced it had been accepted into Databricks’ Built-on Partner Program. The designation follows a review of Intelo.ai’s product and architecture and recognizes its product’s use of the Databricks platform.
Concurrence announced a multi-year partnership with Databricks to bring its Health World Model and AI agents onto the Databricks Data + AI Platform. The companies said the combined offering helps healthcare organizations build longitudinal population records and develop AI applications using their own data.
On September 16, Databricks announced AI initiatives with Singapore’s EDB and IMDA, including a goal to train 20,000 people in data and AI over three years. It also announced a Singapore Startup AI Accelerator, planned to launch in November and scale to support more than 100 startups over three years, working with local universities including NTU, NUS, and SMU.
Databricks made OpenAI GPT-6 Astra available through Unity Gateway on September 4, 2026. The model is positioned for enterprise reasoning, document processing, coding, agentic search, multimodal inputs, and long-context workloads.
Databricks announced The Big Book of AgentOps on September 2, 2026. The guide provides practical guidance on architecture, evaluation, observability, governance, cost management, and deploying reliable AI agents at enterprise scale.
Databricks added Google Gemini 3.8 Flash as a Databricks-hosted model on September 2, 2026. Customers can access it through Databricks Foundation Model APIs.
Databricks added Anthropic Claude Fable 5.1 as a Databricks-hosted model on September 1, 2026. The model is available through Unity Gateway and Databricks Foundation Model APIs.
Databricks launched Genie One web search in beta on September 1, 2026. The feature allows Genie One to search the public web for current information and cite the external sources it uses.
Databricks made Lakebase available in four additional Azure regions: North Central US, France Central, Germany West Central, and East Asia. The expansion broadens the geographic availability of Databricks’ serverless Postgres offering on Azure.
Databricks closed a $5 billion strategic funding round at a $190 billion valuation. The round was led by Coatue alongside Blackstone, MGX, T. Rowe Price, and Sixth Street Growth, and the company said it had surpassed a $7 billion revenue run-rate while growing more than 80% year over year.
Databricks announced that Electric is joining the company to bring WASM Postgres to AI-agent sandboxes. A contemporaneous public announcement characterized the transaction as Databricks acquiring Electric; financial terms were not reported.
Databricks announced that Kimi K3 from Moonshot AI is now available on its platform through Unity AI Gateway. The open-weight model is hosted initially in the United States and is offered with unified API access, governance, cost controls, guardrails, and observability.
Databricks released OfficeQA Pro V2, a benchmark for evaluating enterprise grounded reasoning over unfamiliar, enterprise-style data. The benchmark is based on roughly 1,400 U.S. Treasury PDFs spanning approximately 120,000 pages and was made publicly available for AI practitioners.
Databricks and Microsoft announced an expansion of their decade-long strategic partnership on July 23, 2026, extending into the 2030s. The companies will deepen Azure Databricks integration, expand use of Databricks Genie and Unity AI Gateway across Microsoft products, and bring business-contextual AI capabilities into enterprise workflows.
Databricks announced support for Meta’s Muse Spark 1.1 through Model Provider Services in Unity AI Gateway. The integration provides governed access, permissions, usage controls, and observability for the newly released model through Databricks.
Active Roles
899Business Model
Databricks primarily monetizes its cloud data and AI platform through consumption-based pricing built around Databricks Units (DBUs), with compute and storage priced separately. Customers pay for the processing and platform resources they consume rather than provisioning a fixed-capacity system.
Products
Customers
Tech Stack
Similar Companies
Competitors
Key Investors
Barclays, JPMorgan Chase, Insight Partners