Databricks vs Confluent

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

Confluent leads in AI visibility (95 vs 79)
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
B79
Category Rank
#1 of 2
AI Consensus
58%
Trend
stable
Per Platform
ChatGPT
72
Perplexity
79
Gemini
73

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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Confluent logo

Confluent

LeaderData & Analytics

Data Streaming

Enterprise Kafka platform by Kafka's original creators; $950M revenue growing 25%, powering real-time data pipelines for AI, fraud detection, and event-driven systems.

AI VisibilityBeta
Overall Score
A95
Category Rank
#1 of 1
AI Consensus
66%
Trend
stable
Per Platform
ChatGPT
99
Perplexity
90
Gemini
99

About

Confluent is an enterprise data streaming platform built around Apache Kafka, providing fully managed Kafka infrastructure, stream processing, and data integration capabilities that enable real-time data pipelines and event-driven architectures. Founded in 2014 by Jay Kreps, Jun Rao, and Neha Narkhede — the original creators of Apache Kafka at LinkedIn — Confluent is headquartered in Mountain View, California and listed on NASDAQ with approximately $950 million in annual revenue growing ~25% year-over-year.

Full profile

AI Visibility Head-to-Head

79
Overall Score
95
#1
Category Rank
#1
58
AI Consensus
66
stable
Trend
stable
72
ChatGPT
99
79
Perplexity
90
73
Gemini
99
86
Claude
94
87
Grok
86

Key Details

Category
MLOps
Data Streaming
Tier
Leader
Leader
Entity Type
company
company

Capabilities & Ecosystem

Databricksintegrates withConfluent

Capabilities

Only Databricks
MLOps
Only Confluent
Data Streaming

Integrations

Databricks is classified as company. Confluent is classified as company.

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