The Data and AI Company
Databricks (mosaicml.com) scores 83 out of 100 on Brand Analyzer, placing it in the Strong Brand tier among SaaS brands, Technology brands, in the 80th percentile of 25215 SaaS brands.
Databricks is an American technology company founded in 2013 and headquartered in San Francisco. It provides a unified data intelligence platform that combines data engineering, analytics, and AI/ML capabilities, enabling enterprises to build, deploy, and scale AI agents and applications. The company is led by CEO Ali Ghodsi and targets enterprise data teams, data scientists, and ML engineers seeking to unify data, analytics, and AI on a single platform.
| Brand Name | Databricks |
|---|---|
| Domain | mosaicml.com |
| Industry | SaaS, Technology |
| Founded | 2013 |
| Headquarters | San Francisco |
| CEO | Ali Ghodsi |
| Main Competitors | Snowflake (93/100), Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure, Cloudera (83/100), Palantir (88/100), DataRobot (86/100) |
Moz Domain Authority 43/100 vs category average 37 / leader 100 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
Ranked #868,756 on the Tranco list of most-visited sites - modest traffic makes the brand easy for AI models to overlook.
Databricks has a dedicated Wikipedia entity - a top-weighted signal AI models rely on to identify and describe the brand.
The homepage meta description reads "Read the Databricks Databricks AI category on the company blog for the latest employee stories and events." (Meta description: 17 words (ideal length). OG description present and descriptive) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: og:title, og:description, og:image, og:type, Twitter cards, canonical. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: No robots.txt found (default: all bots allowed, but explicit file preferred) - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Detected tech stack: Cloudflare, Gatsby.
Social footprint: verified profiles on LinkedIn, X (Twitter), YouTube, Instagram, GitHub; no detected presence on Facebook - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is Databricks?", Claude could identify the brand as of September 2026. MosaicML was a startup known for efficient large language model training tools and infrastructure, and it was acquired by Databricks in 2023 to bolster Databricks' generative AI offerings. Best known for Efficient, cost-effective training of large language models, later acquired by Databricks.
When asked "Best brands similar to Databricks?", Claude would recommend Databricks as of September 2026. It's a notable example of AI infrastructure innovation and its acquisition is relevant when discussing Databricks' AI capabilities or LLM training platforms.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
Databricks's main competitors in SaaS: Snowflake (93/100), Cloudera (83/100), Palantir (88/100), DataRobot (86/100).
Sources: Brand Analyzer scan
Databricks is an American technology company founded in 2013 and headquartered in San Francisco. It is classified as a SaaS/technology company that offers a unified data intelligence platform combining data engineering, analytics, and artificial intelligence capabilities for enterprises.
Sources: Databricks official site
Databricks has moderate AI-search visibility, scoring 55/100 on Brand Analyzer's AI visibility composite (visibility 70, trust 29, recommendation 59). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: Databricks official site
Databricks was founded in 2013. Databricks operates in the SaaS category. It is analyzed by Brand Analyzer across seven brand dimensions and AI-search visibility.
Sources: Wikidata
Databricks is headquartered in San Francisco. Databricks operates in the SaaS category.
Sources: Wikidata
Databricks provides a unified data intelligence platform that combines data engineering, analytics, and AI/ML capabilities. It enables organizations to build, deploy, and scale AI agents and applications by unifying their data, analytics, and AI workflows on a single platform.
Sources: Databricks official site
Databricks offers a unified data intelligence platform that integrates data engineering, analytics, and AI/ML capabilities, supporting the building, deployment, and scaling of AI agents and applications for enterprises.
Sources: Databricks official site
Databricks scores 59/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest SaaS options. Recommendation depends on crawlability, structured data, and category authority; a Wikipedia presence helps.
Sources: Databricks official site
Databricks can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: Databricks official site
Databricks is used by enterprise data teams, data scientists, ML engineers, and organizations seeking to build and scale AI and analytics solutions.
Sources: Databricks official site
Databricks is known for its unified data intelligence platform that merges data engineering, analytics, and AI/ML into a single environment, positioning itself as a leading platform for enterprise data and generative AI solutions.
Sources: Databricks official site
Databricks is popular because it offers a unified platform that consolidates data engineering, analytics, and AI/ML capabilities, allowing enterprise data teams to efficiently build, deploy, and scale AI agents and applications rather than using multiple disparate tools.
Sources: Databricks official site
Databricks scores 55/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
Databricks has a limited AI-visibility profile at 55/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is visibility (70/100) and its weakest is trust (29/100). It benefits from a recognised Wikipedia company entity, a Wikidata knowledge-graph entry and a global traffic rank of #868,756 (Tranco). The main gaps holding it back: thin schema.org structured data and no llms.txt to steer AI to its best pages. In a live check, Claude could already identify Databricks from memory (September 2026) - a sign these signals are paying off.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
Ranked closest to Databricks: Mosaic (83/100), Moovit (83/100), MotionPoint (83/100), MotorCheck (83/100).
A step up - brands to learn from: Zuken (91/100), ZipRecruiter (91/100).
Category leader: Hostinger (97/100).
Brand Analyzer is built by DataEase AI. Track your brand in ChatGPT, Gemini and Perplexity.