Databricks vs VAST Data
Side-by-side comparison of AI visibility scores, market position, and capabilities
$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.
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.
Closed a $1 billion Series F at a $30 billion valuation in April 2026, backed by NVIDIA and Fidelity, after surpassing $500M in committed ARR with its AI Operating System platform.
About
VAST Data builds the AI Operating System — a unified platform combining all-flash storage (DataStore), an AI-native database (DataBase), and a globally distributed namespace (DataSpace) into a single infrastructure stack. The platform is purpose-built for organizations training, running, and managing AI models and agents at scale. In 2026, VAST launched AgentEngine, a production-grade deployment layer for multi-agent AI stacks with full auditability and MCP integration.
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