Apache Superset vs Grafana: Which Free Dashboard Tool Fits Your Team?

A factual comparison of Apache Superset and Grafana — two free, open-source dashboarding tools built for very different jobs: business intelligence vs infrastructure monitoring.

Updated 2026-10 · 2026

Apache Superset

Open-source data exploration and visualization for BI teams

Freeopen source, self-hosted

Strengths

+SQL Lab lets you write and explore queries directly against your database
+40+ chart types including pivot tables, geospatial maps, and heatmaps
+Native row-level security and role-based access control

Weaknesses

-Not built for real-time/streaming metrics — relies on polling and refresh intervals
-No native support for logs or distributed traces
-Smaller plugin ecosystem for infra/ops monitoring

Best for

Data and BI teams who want free, SQL-native dashboards over a data warehouse

Grafana

Open-source observability and metrics dashboarding platform

Freeopen source (OSS), self-hosted

Strengths

+Best-in-class for time-series dashboards (Prometheus, InfluxDB, Loki, Tempo)
+Unified alerting engine with multi-condition rules and routing to Slack/PagerDuty/email
+Huge plugin ecosystem — 100+ official and community data sources

Weaknesses

-Weaker for ad-hoc SQL/BI-style analysis — no pivot tables or deep joins
-Query editor differs per data source, adds learning curve
-Advanced reporting and some RBAC features gated behind Grafana Enterprise/Cloud

Best for

DevOps/SRE teams monitoring infrastructure metrics, logs, and traces in near real time

Feature Comparison

Feature	Apache Superset	Grafana
Primary use case	Business intelligence & data exploration	Infrastructure/observability monitoring
Data sources	40+ SQL databases via SQLAlchemy	100+ sources incl. Prometheus, Loki, Elasticsearch, SQL
Visualization types	40+ chart types incl. maps & pivot tables	Time-series panels, heatmaps, logs, traces
Alerting	Alerts & Reports (threshold-based, email/Slack)	Unified alerting engine with multi-condition routing
Real-time data	Polling/refresh-based	Near real-time streaming panels
SQL support	Full SQL Lab IDE built in	Query editor varies per data source, limited raw SQL
Row-level security	Native RLS	Limited, mostly via data source permissions
Licensing	Apache 2.0	AGPLv3 (core), Enterprise plugins proprietary
Hosting options	Self-host or Preset.io managed	Self-host (OSS) or Grafana Cloud
Logs & traces support	None	Native via Loki/Tempo
Embedding dashboards	Supports embedded/guest tokens	Supports embedding, public dashboards (beta)

The Verdict

These tools solve different problems despite both being free dashboard builders — Superset is a BI tool for querying and exploring structured data, Grafana is an observability tool for watching metrics, logs, and traces in real time. Don't replace one with the other unless your actual workload has shifted from analytics to operations monitoring; many teams end up running both side by side.

How to switch from Apache Superset to Grafana

1Export your Superset dashboards and charts via Dashboard > Export or the CLI command `superset export-dashboards -f export.zip`, which produces a ZIP of YAML files describing charts, datasets, and layout (not raw data).
2Inventory your underlying databases/warehouses and register each as a Grafana data source using the same connection credentials Superset used.
3Recreate your most-used Superset charts as Grafana panels, translating each SQL query into Grafana's query editor for that data source type.
4Rebuild Superset's Alerts & Reports schedules as Grafana alert rules and notification policies routed to Slack, email, or PagerDuty.
5Set up Grafana folders and team-based RBAC to mirror the role-based dashboard access you had in Superset before rolling out to the team.
6Run both tools in parallel for 1-2 weeks, verify dashboard accuracy against Superset, then redirect links and decommission unused Superset instances.

Apache Superset vs Grafana: common questions

How do I export my dashboards and charts from Apache Superset?+

Superset lets you export dashboards and charts as a ZIP file of YAML config via the UI's Export option or the CLI command `superset export-dashboards -f export.zip`. This exports metadata and layout, not raw data, since Superset queries live databases. You'll need to manually rebuild the equivalent panels in Grafana since the YAML format isn't compatible.

What features will I lose moving from Superset to Grafana?+

You'll lose Superset's SQL Lab IDE, pivot tables, and tightly integrated row-level security tied to query results. Grafana has no equivalent for ad-hoc BI-style reporting or complex joins across datasets. Many teams end up keeping Superset for analytics and adding Grafana only for infra monitoring rather than fully switching.

Is Grafana's free tier enough for a small team?+

Grafana OSS self-hosted is completely free with no feature caps, so it works for teams of any size. If you use Grafana Cloud instead, the free tier includes 10k metric series, 50GB logs, 50GB traces, and 3 users — usually enough for a small team's monitoring needs. Beyond that, usage-based charges kick in on the Pro plan.

Does Grafana support the same database integrations as Superset?+

Grafana supports SQL data sources like PostgreSQL and MySQL, so you can point it at the same databases Superset used. But its query builder is less suited to complex joins and exploratory SQL than Superset's SQL Lab, so pure BI reporting is harder to replicate 1:1.

Is Grafana cheaper than Superset long term?+

Both are free when self-hosted, so there's no inherent cost difference unless you choose managed hosting — Preset.io for Superset or Grafana Cloud for Grafana. Grafana Cloud's usage-based pricing can grow quickly with high-cardinality metrics or long retention windows, while Preset.io charges per seat instead.