Apache Superset and Redash are two open source BI and SQL data exploration platforms. Both free, but with different philosophies: Superset emphasizes rich dashboards, Redash focuses on ad-hoc exploration and query sharing. This article compares their positioning, strengths, and limitations to help you choose in 2026.
1. Overview
Apache Superset is an Apache Foundation project, launched in 2015 by Airbnb. It targets a complete BI platform: dashboards, rich charts, RLS, embedded.
Redash was created in 2013 by Arik Fraimovich. Acquired by Databricks in 2020, its upstream development has slowed, but the project remains open source and used by thousands of teams.
If you want to test Apache Superset without going through installation, TVL Managed Superset deploys a ready instance in less than 3 minutes.
2. Compared philosophy
| Aspect | Apache Superset | Redash |
|---|---|---|
| Approach | Complete dashboards and BI | Query first, dashboards as bonus |
| Visualizations | 50+ types, rich | 20+ types, simpler |
| SQL Editor | Powerful SQL Lab | Central editor, historical strength |
| Model | Datasets + slices + dashboards | Queries + visualizations + dashboards |
| Target audience | Data analysts, BI | Data analysts, fast exploration |
3. Features
| Feature | Superset | Redash |
|---|---|---|
| Visual question builder | Limited | No (SQL only) |
| Advanced SQL Editor | Excellent (SQL Lab) | Excellent (product core) |
| Chart types | 50+ | 20+ |
| Cross-filtering | Yes | Limited |
| Row Level Security | Yes | No |
| SSO (OIDC, SAML) | Yes | Limited (Google, basic SAML) |
| Alerts and schedules | Yes (Celery beat) | Yes |
| REST API | Yes | Yes |
| Native connectors | 40+ | 40+ |
| Embedded analytics | Yes (official SDK) | Limited (iframe) |
4. Community and activity
| Metric | Apache Superset | Redash |
|---|---|---|
| GitHub stars | ~63,000 | ~26,000 |
| Releases/year | 10-15 | 1-3 (since Databricks acquisition) |
| Active contributors | ~1,800 | ~300 |
| Model | Apache Software Foundation | OSS sponsored by Databricks |
The activity gap is significant: Superset publishes frequent releases with new features, Redash evolves more slowly since 2020.
5. Performance and scale
Both tools delegate computation to the underlying database. Superset benefits from a more modern architecture (Celery workers, Redis cache, async queries) that scales better for heavy dashboards. Redash remains excellent for solo analyst ad-hoc exploration.
6. Hosting and operations
Redash is lighter: minimal Docker compose, fewer components. Superset is more demanding but benefits from a mature official Helm chart and professional managed services. See also how to host Apache Superset. This configuration is applied by default on TVL Managed Superset, which follows community best practices.
7. When to choose Apache Superset?
- You want rich dashboards shared across the company;
- You need RLS, SSO, audit trail without paying;
- Your data stack includes modern analytical databases (ClickHouse, DuckDB);
- You want an actively developed and well-governed project;
- You're looking for embedded analytics for a SaaS product.
8. When to choose Redash?
- You have a small data team mostly doing ad-hoc SQL exploration;
- You want a simple tool to deploy and operate;
- Rich dashboards aren't the priority;
- You prefer the Databricks ecosystem (native integration).
9. Migrating from Redash to Superset
There's no official import tool. Migration is manual:
- Recreate data sources in Superset;
- Copy SQL queries to SQL Lab;
- Save queries as virtual datasets;
- Recreate visualizations and dashboards.
Plan 1-2 days for 30-50 dashboards.
10. Conclusion
In 2026, Apache Superset has established itself as the open source reference for complete BI. Redash remains an excellent ad-hoc SQL exploration tool, but development dynamics and feature richness now clearly tilt toward Superset.
Want the benefits of Apache Superset without the friction of installation and maintenance? Deploy your instance in 3 clicks with TVL Managed Superset, hosted in Europe (OVHcloud, Roubaix, France).
For more: vs Metabase, vs Tableau, what is Apache Superset?.