Databricks
Databricks provides a unified platform for enterprise data analytics and AI.
Founded
2013Databricks provides a unified platform for enterprise data analytics and AI.
Databricks combines an open lakehouse foundation with data governance and AI capabilities in one platform. Its architecture lets teams use organizational data across analytics, machine learning, applications, and agent systems.
The company also reports more than 1,200 global cloud, software, and consulting partners. That ecosystem supports joint customers as they scale data, analytics, and AI initiatives across preferred cloud environments.
Source: databricks.com
The platform combines data engineering, analytics, and artificial intelligence workloads, so deployments can require governance and operational coordination across several product areas. Databricks describes customer-selected cloud deployment and usage-based services; teams should evaluate the required cloud services, workload configuration, and consumption against their own operating needs.
Its published pricing is usage-based rather than a single fixed platform price. The service mix, cloud infrastructure, and consumption level affect total cost, so customers typically assess workload design and commitments when budgeting for the platform.
Source: databricks.com
The current site crawl shows a 14-day full trial, a Free Edition for students and developers, and usage-based pricing; its contact page solicits product and pricing inquiries and the site lists partner principles. This supports self-serve evaluation plus contact-led and partner channels, though the crawl exposes no current sales-role mix or count.
A current Databricks LinkedIn company-profile capture reports 1,400,940 followers; ten displayed updates dated September 29–October 4, 2026 received 93–404 likes and 2–20 comments apiece. That is measured owned-social reach and engagement; the captured profile supplies no paid-ad impression count or creator-campaign reach measure.
Source: databricks.com
Databricks publishes a dedicated Databricks-versus-Snowflake comparison, identifying a direct platform matchup in its current sales materials. That documented head-to-head supports high rivalry.
Databricks' company materials identify Apache Spark, Delta Lake and MLflow as technologies from an open-source ecosystem. Existing open-source components can lower the technical cost of building competing services, though the sources reviewed provide no measured entry-cost or entrant-count data; threat of new entrants is medium.
The official Databricks-versus-Snowflake comparison documents Snowflake as an alternative in data-platform purchasing. The reviewed sources do not measure workload substitution or customer switching, so substitute pressure is medium.
Databricks' pricing page offers pay-as-you-go billing and committed-use discounts, while its contact page invites product and pricing inquiries. These published routes document purchasing flexibility, but no reviewed source measures buyer concentration or negotiating outcomes; buyer power is medium.
Databricks' pricing materials describe compute-cost estimates across clouds, and its company materials say customers deploy workloads on major cloud providers. That reliance gives infrastructure suppliers a role, but the reviewed sources do not quantify cloud spend or supplier terms; supplier power is medium.
Source: databricks.com
Databricks reported more than 20,000 customer organizations and said over 1,000 customers were consuming at annualized rates above $1 million. More than 100 customers were consuming at rates above $10 million.
Its August 2026 update also reported more than 80% annual growth, a $7 billion revenue run-rate, and positive adjusted free cash flow. Lakehouse and Lakebase each reached separate product revenue milestones, indicating growth across data and AI workloads.
Source: databricks.com
The Databricks Data + AI Platform spans data ingestion and engineering, data warehousing, analytics, machine learning, application development, data sharing and governance. Official product navigation describes product families including Lakeflow, Lakehouse, Lakebase, Genie, Unity Catalog, Databricks Apps, AI/BI, Marketplace, Lakewatch, OpenSharing, and CustomerLake.
Company materials report more than 20,000 customer organizations worldwide and deployments across major cloud providers. Product terms, availability, implementation requirements and consumption-based charges vary by offering and should be confirmed from the relevant current product and pricing documentation.
Source: databricks.com
Databricks offers pay-as-you-go pricing with no upfront cost and bills products at per-second granularity. Customers select services across the platform and pay for the products they use.
The company also offers committed-use contracts that exchange usage commitments for discounts and other benefits. Larger commitments can provide greater benefits and flexible use across multiple cloud providers.
Source: databricks.com
A current LinkedIn company profile capture reports 1,400,940 followers and 17,109 employees. These measured audience and workforce figures establish scale without relying on projected or unaudited operating estimates.
The same profile labels Databricks privately held, and the reviewed public materials provide no paid-ad impression count or customer-acquisition-cost measure. That leaves public assessment of commercial efficiency limited; the missing measures are not evidence of poor performance.
Databricks' official site lists a Free Edition for students and developers and a 14-day full trial. Those documented no-cost evaluation paths create an opportunity to reach prospective platform users before paid use, although the reviewed sources report no trial-conversion count.
Databricks' current site crawl lists a dedicated Databricks-versus-Snowflake comparison page, identifying a named competitor in the same data-platform buying process. The reviewed sources provide no displacement or win-rate figures, so competitive impact is not quantified.
Source: databricks.com
Databricks provides a Data + AI Platform built on an open lakehouse architecture that unifies data, governance, analytics, and AI workloads. It supports technical teams building and deploying secure data and AI applications.
The platform serves more than 20,000 organizations worldwide, including 70% of the Fortune 500. Databricks says customers use it to control enterprise data and apply that data to AI.
Source: databricks.com