pgHero vs MonPG: Point-in-Time Dashboard vs Continuous Monitoring

pgHero is one of the best answers ever written to the question “what is slow right now?” – a single open-source dashboard over pg_stat_statements that deploys in minutes. The question it does not try to answer is “what changed since Tuesday, and is it getting worse?” That is the line between a status page and a monitoring system, and it is the line this comparison walks.

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Strongest fit

• You need history: query performance trended over weeks, so regressions are caught by comparison, not by memory.
• You need alerting – pgHero has no built-in alerts, so something else has to wake you up.
• Several engineers share triage and you want everyone looking at the same ranked evidence, not a screenshot in Slack.
• You want index suggestions weighted by production risk, not just a list of unused and missing indexes.

Not ideal when

• You want a free, self-hosted, zero-vendor dashboard you can deploy this afternoon – pgHero genuinely delivers that, and for a single small database it may be all you need.
• Your stack is Rails and you like pgHero’s native gem integration with the app you already operate.
• You only check database health when something feels off, and a point-in-time view fits how you actually work.

Decision signals to evaluate

• History: pgHero shows current pg_stat_statements state; MonPG stores trends, so ‘this query is 4x slower than last week’ is a query, not an investigation.
• Alerting: pgHero ships none; MonPG alerts on regressions, locks, vacuum debt, and connection saturation.
• Index advice: pgHero lists unused/missing indexes; MonPG adds rollout risk modeling and migration SQL with a rollback plan.
• Operating cost: pgHero is free software you run and patch; MonPG is a paid service with the ops handled.
• Scale: pgHero is per-database; MonPG gives one surface across all your instances and replicas.
• Incident depth: when pgHero shows a slow query, your next step is manual EXPLAIN work; MonPG carries you into plan and lock context directly.

Related PostgreSQL pages

• PostgreSQL Slow Query Monitoring — Catching regressions by trend, not by memory.
• PostgreSQL Index Rollout — From index suggestion to production-safe DDL.
• Self-Hosted PostgreSQL Monitoring — Operational patterns for self-managed instances.

FAQ

Is pgHero good enough for production?

For a single database with light traffic and an engineer who checks it regularly – honestly, yes. The failure mode is growth: more databases, more engineers, incidents at 3am with no alerting and no history. Teams usually outgrow pgHero at the first regression nobody noticed for a week.

Can I keep pgHero and add MonPG?

Yes. Both read from pg_stat_statements without conflict. Some teams keep pgHero as a quick local view for developers and use MonPG for alerting, history, and incident triage.

Why pay for monitoring when pgHero is free?

You are not paying for charts – you are paying for retention, alerting, regression detection, and rollout safety that pgHero deliberately does not include. If those gaps cost you one bad incident a quarter, the math usually closes quickly. If they never bite, keep pgHero.

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.