Tabular vs Databricks

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

Databricks leads in AI visibility (93 vs 35)
Tabular logo

Tabular

NicheData & Analytics

Managed Apache Iceberg Data Lakehouse Platform

Tabular built a fully managed Apache Iceberg platform for scalable data lakes; founded by the creators of Apache Iceberg; acquired by Databricks in June 2024 for a reported $2B; its technology underpins Databricks' lakehouse strategy.

AI VisibilityBeta
Overall Score
D35
Category Rank
#141 of 161
AI Consensus
74%
Trend
stable
Per Platform
ChatGPT
40
Perplexity
38
Gemini
35

About

Tabular was a data infrastructure company founded in 2021 by Ryan Blue, Daniel Weeks, and Jason Reid — the same engineers at Netflix who created the Apache Iceberg open table format — and was headquartered in San Francisco, California. The company built a fully managed platform for Apache Iceberg that allowed organizations to construct scalable, high-performance data lakehouses without managing the operational complexity of Iceberg's catalog, storage optimization, and access control layers themselves.

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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.

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AI Visibility Head-to-Head

35
Overall Score
93
#141
Category Rank
#1
74
AI Consensus
83
stable
Trend
stable
40
ChatGPT
90
38
Perplexity
91
35
Gemini
93
33
Claude
96
29
Grok
89

Key Details

Category
Managed Apache Iceberg Data Lakehouse Platform
MLOps
Tier
Niche
Leader
Entity Type
brand
company

Capabilities & Ecosystem

Capabilities

Only Databricks
MLOps
Databricks is classified as company.

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