Grafana Loki vs Prometheus
| Tagline | Horizontally scalable log aggregation system designed to work with Grafana | Industry-standard metrics monitoring and alerting toolkit with PromQL |
| Category | Monitoring & Status Pages | Monitoring & Status Pages |
| Replaces | Datadog, Statuspage | Datadog |
| GitHub stars | 24k | 65k |
| Language | Go | Go |
| License | AGPL-3.0 | Apache-2.0 |
| Self-host difficulty | 3/5 Moderate | 4/5 Involved |
| Deploy options | Docker Docker Compose Kubernetes | Docker Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 5 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 Loki
- Full-text search is not supported; only label-based log filtering
- Requires Grafana for a usable query UI (no standalone dashboard)
- Scalable distributed mode requires object storage (S3/GCS) and careful tuning
Prometheus
- No built-in dashboards UI; you must pair it with Grafana
- Long-term storage and horizontal scale need add-ons (Thanos, Cortex, Mimir)
- No logs, traces, or APM out of the box (metrics only)
- Steeper operational learning curve than turnkey Datadog
Bottom line
Choose Grafana Loki if you want the lower-effort setup; choose Prometheus for the larger community and ecosystem. Prometheus has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Grafana Loki
Horizontally scalable log aggregation system designed to work with Grafana