Jaeger vs Prometheus
| Tagline | Distributed tracing system for monitoring microservice latency and dependencies | Industry-standard metrics monitoring and alerting toolkit with PromQL |
| Category | Monitoring & Status Pages | Monitoring & Status Pages |
| Replaces | Datadog, Pingdom | Datadog |
| GitHub stars | 23k | 66k |
| Language | Go | Go |
| License | Apache-2.0 | 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 | yesterday | yesterday |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Jaeger
- Tracing only; no metrics or log aggregation built in
- Production deployments require Cassandra or Elasticsearch for storage at scale
- UI is functional but less polished than commercial APM products
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 Jaeger if you want the lower-effort setup; choose Prometheus for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.
Jaeger
Distributed tracing system for monitoring microservice latency and dependencies