Can I keep Grafana after adopting MonPG?
Yes. Teams often keep Grafana for broad telemetry and use MonPG where PostgreSQL depth and speed matter most.
Comparison Guide
Grafana and Prometheus vs MonPG for PostgreSQL
Grafana and Prometheus are flexible, but PostgreSQL operations often require significant custom query design and maintenance. MonPG trades flexibility for faster time-to-decision.
Strongest fit
- You want fast operational value without dashboard engineering backlog.
- You need query + index + planner context packaged for incidents.
- You prefer opinionated defaults for PostgreSQL triage.
Not ideal when
- You need total metric pipeline control and can maintain it long-term.
- You already have mature PostgreSQL runbooks built on Prometheus data.
Decision signals to evaluate
Cost of maintaining custom PostgreSQL dashboards and alerts.
Time to train new engineers on your custom observability stack.
Coverage of DB-specific signals without manual curation.
Related PostgreSQL pages
FAQ
Is vendor lock-in higher with managed tooling?
Operationally, the key factor is exportability of decisions and evidence. MonPG keeps workflows grounded in PostgreSQL-native signals.
More comparisons
pgvectorBench vs MonPG HNSW Tuning Lab
Compare pgvectorBench, the open-source CLI, with MonPG HNSW Tuning Lab. Hosted benchmark, migration SQL, CI integration, and team sharing vs. a local-only script runner.
pganalyze vs MonPG
Technical comparison of pganalyze and MonPG for PostgreSQL monitoring, query performance triage, index rollout, and production diagnostics.
Datadog vs MonPG
Comparison of Datadog and MonPG for teams that need PostgreSQL-first diagnostics, query insights, and database-specific operations workflows.
New Relic vs MonPG
Comparison of New Relic and MonPG for production PostgreSQL teams focused on query behavior, planner regressions, and operational triage.