Domo vs Apache Superset

Domo is a cloud business intelligence platform founded in 2010 in Utah by Josh James, co-founder of Omniture, and listed on Nasdaq in 2018. It combines data integration, dashboards, low-code apps and AI in one hosted product aimed at business teams, not only analysts. In September 2026 Progress Software completed a $400 million acquisition of Domo's AI and data platform business, so Domo now sits inside Progress's data portfolio.

The platform includes 1,000+ prebuilt connectors, drag-and-drop Magic ETL, Cloud Amplifier for querying Snowflake, BigQuery or Databricks without copying data, charts and dashboards, scheduled reports and alerts, App Studio for low-code data apps, embedded analytics for customer-facing reporting, workflows and AI agents with governed model management. Pricing is credit-based: you buy a pool of credits consumed by storage, data refreshes, workflows and AI, with unlimited users and a 30-day free trial.

Domo fits mid-size and large companies that want one vendor for pipelines and dashboards and value mobile, executive-friendly reporting. Power BI is far cheaper for Microsoft shops, Tableau has deeper visual analytics, and Looker Studio or Metabase cover simpler needs for little or no cost. Credit consumption can be hard to forecast, and independent estimates put typical contracts in the tens of thousands of dollars per year.

Buying tip: because of the Progress acquisition, ask about roadmap, support continuity and contract terms before renewing or signing a multi-year deal, and model credit burn on your real refresh schedules during the trial.

Apache Superset is an open-source data exploration and visualization platform, originally created at Airbnb by Maxime Beauchemin in 2015 and graduated to a top-level project of the Apache Software Foundation in 2021. It is used by data teams at many large companies as a self-hosted alternative to commercial business intelligence tools, and Preset, a company founded by Superset's creator, offers it as a managed cloud service.

Superset connects to almost any SQL-speaking database through SQLAlchemy, including PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, ClickHouse, Druid, Trino and Databricks. Analysts can write queries in SQL Lab, a browser-based SQL IDE, or use the no-code chart builder with more than 40 visualization types, from tables and time series to maps and Sankey diagrams. Charts are combined into interactive dashboards with cross-filters and native filters. A lightweight semantic layer defines datasets, metrics and calculated columns, and role-based access control, row-level security, caching, alerts and reports support production use. The software itself is free under the Apache 2.0 license; costs come from infrastructure and engineering time, or from Preset's paid plans.

Superset fits organizations with data engineers who want scalable, vendor-neutral BI without per-user licenses. Setup, upgrades and security configuration require technical skills, and the interface is less approachable for business users. Metabase is easier for non-technical teams, Looker and Power BI offer stronger governed modeling with commercial support.