Grafana vs Homer
| Tagline | Observability and analytics dashboards for metrics, logs, and time series | Dead simple static homepage to expose your server services via YAML config |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI, Datadog | Tableau, Looker, Power BI |
| GitHub stars | 74k | 11k |
| Language | TypeScript | Docker |
| License | AGPL-3.0 | Apache-2.0 |
| Self-host difficulty | 2/5 Easy | 2/5 Easy |
| Deploy options | One-Click Docker Docker Compose Kubernetes Manual | Docker Docker Compose Manual |
| Managed hosting | ||
| Last updated | today | 2 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Grafana
- Oriented toward time-series and observability, not ad-hoc business analytics or pivot-style exploration
- No business-friendly visual query builder; dashboards assume knowledge of data sources and query languages
- Weak at relational/tabular BI reporting compared to Tableau or Power BI
- No semantic modeling layer; data modeling lives in the underlying sources
Homer
- Extremely minimal: no service widgets, no data pulled from APIs beyond ping checks
- No built-in authentication or user management
- No analytics, charts, or data visualization features
- Configuration is file-only with no web UI editor
Bottom line
Both are a similar lift to self-host; choose Grafana for the larger community and ecosystem. Grafana has seen more recent development. Open each guide below for deploy steps and the full feature gap.