data.world vs Databricks

Side-by-side comparison of AI visibility scores, market position, and capabilities

Databricks leads in AI visibility (93 vs 53)
data.world logo

data.world

GrowthData Catalog

Enterprise Data Catalog & Knowledge Graph

data.world is an enterprise data catalog and knowledge graph platform that connects data assets with business context for governed, AI-ready data management.

AI VisibilityBeta
Overall Score
C53
Category Rank
#79 of 161
AI Consensus
80%
Trend
stable
Per Platform
ChatGPT
52
Perplexity
50
Gemini
52

About

data.world is an enterprise data catalog and knowledge graph platform that represents the data landscape as a connected graph of relationships between data assets, business concepts, people, and processes — enabling organizations to answer not only "where is this data?" but "how does this data relate to our business concepts, who owns it, what policies govern it, and which other assets does it affect?" The platform's knowledge graph architecture stores metadata in a graph structure that can represent the rich interconnections between entities in the data environment more naturally than tabular catalog storage, making it possible to query the catalog with graph traversal logic that discovers relationships and dependencies that flat catalog structures cannot navigate. This approach is particularly valuable for organizations building AI applications that need richly connected contextual metadata to ground language model responses in accurate organizational knowledge.

Full profile
Databricks logo

Databricks

LeaderData & Analytics

MLOps

$4.8B revenue run-rate; 55% YoY growth; $134B valuation (Series L). Mosaic AI for enterprise LLM fine-tuning and inference; Unity Catalog for data governance. DBRX open-source model; every major enterprise AI deployment runs on the lakehouse.

AI VisibilityBeta
Overall Score
A93
Category Rank
#1 of 161
AI Consensus
83%
Trend
stable
Per Platform
ChatGPT
90
Perplexity
91
Gemini
93

About

Databricks was founded in 2013 by the original creators of Apache Spark — Ali Ghodsi, Matei Zaharia, and five other UC Berkeley researchers — to unify data engineering, analytics, and machine learning on a single platform. The company commercialized the lakehouse architecture, combining the flexibility of data lakes with the reliability of data warehouses. Databricks runs on AWS, Azure, and GCP and leads the commercial distribution of the open-source Delta Lake and MLflow projects.\n\nThe platform includes the Databricks Lakehouse for unified data processing, Unity Catalog for governance and lineage tracking, and Mosaic AI for enterprise LLM fine-tuning, model serving, and generative AI application development. It supports data engineering, SQL analytics, BI, feature engineering, and model training within a single governance perimeter, serving enterprises in financial services, healthcare, manufacturing, and media.\n\nDatabricks achieved a $4.8 billion annualized revenue run-rate in early 2025 with 55% year-over-year growth and a $62 billion valuation from its Series L round — one of the most valuable private software companies globally. Its dual role as the leading commercial lakehouse vendor and steward of influential open-source projects gives it a unique ecosystem advantage as enterprises accelerate investment in AI infrastructure.

Full profile

AI Visibility Head-to-Head

53
Overall Score
93
#79
Category Rank
#1
80
AI Consensus
83
stable
Trend
stable
52
ChatGPT
90
50
Perplexity
91
52
Gemini
93
58
Claude
96
56
Grok
89

Key Details

Category
Enterprise Data Catalog & Knowledge Graph
MLOps
Tier
Growth
Leader
Entity Type
brand
company

Capabilities & Ecosystem

Capabilities

Only data.world
Enterprise Data Catalog & Knowledge Graph
Only Databricks
MLOps
Databricks is classified as company.

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