Apache Superset vs Databricks
Side-by-side comparison of AI visibility scores, market position, and capabilities
Apache Foundation open-source BI and data visualization platform; widely deployed by enterprises and cloud providers as a self-hosted analytics layer.
About
Apache Superset is an open-source business intelligence and data visualization platform originally created at Airbnb in 2015 by Maxime Beauchemin and donated to the Apache Software Foundation in 2017, where it graduated as a top-level Apache project in 2021. Superset was built to provide Airbnb's data analysts with a self-service SQL query environment and interactive dashboard builder connected directly to their data infrastructure. Its open-source, self-hosted nature made it attractive to organizations that needed a powerful BI tool without the per-seat licensing costs of commercial alternatives like Tableau or Looker.\n\nApache Superset has become one of the most widely deployed open-source BI platforms globally, with contributions from hundreds of developers and production deployments at companies including Airbnb, Lyft, Twitter (now X), Dropbox, and many others. Preset, a company founded by Maxime Beauchemin, provides a managed cloud version of Superset with enterprise support, making it accessible to organizations that want Superset's capabilities without running their own infrastructure. The platform's active community continuously adds new chart types, database connectors, and features, keeping it competitive with commercial offerings.\n\nSuperset's feature set includes a SQL Lab for ad hoc query writing and exploration, a drag-and-drop dashboard builder with more than 40 chart types, semantic layer support via datasets with metrics and dimensions, and role-based access control for governing who can access which data and dashboards. It connects to more than 40 databases and query engines including Snowflake, BigQuery, Redshift, Databricks, ClickHouse, Druid, Presto, Trino, and standard SQL databases, making it one of the most broadly compatible BI tools available.
$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.
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