Azure Query Performance Insight vs MonPG for Flexible Server

Query Performance Insight is the portal view over Query Store on Azure Database for PostgreSQL: top queries by duration or executions, aggregated into time buckets, with about a week of history by default. As a free first look it is exactly right. The limits show up in the aggregation – 15-minute buckets hide spikes, per-database scope hides fleet patterns, and there is no path from ‘this query is slow’ to ‘here is the plan, the lock chain, and the fix’.

Start trial Read PostgreSQL guide

Strongest fit

• You need spike-level granularity – QPI’s aggregation windows smooth over exactly the short-lived events that cause pages.
• You need history past Query Store’s default retention, kept off the database server’s own storage budget.
• You want alerting on regressions and saturation; QPI is a portal view, not an alerting system.
• You run more than one server (or more than one cloud) and want one surface instead of per-resource portal blades.

Not ideal when

• You want a free, zero-install view that is already in the portal you use – QPI requires only enabling Query Store, and that convenience is real.
• Your databases are small and quiet enough that weekly top-query review covers your actual risk.
• Organizational policy keeps all tooling inside the Azure portal and Azure Monitor.

Decision signals to evaluate

• Granularity: QPI aggregates into coarse time buckets; MonPG keeps per-query-fingerprint trends fine enough to see a deploy’s immediate effect.
• Retention: Query Store defaults to about 7 days and competes for server storage; MonPG retention lives off-instance.
• Scope: QPI is per database; MonPG aggregates servers, replicas, and clouds on one surface.
• Alerting: QPI has none of its own (you assemble Azure Monitor alerts separately); MonPG ships database-aware alerts.
• Depth: QPI ends at ‘this query was slow’; MonPG continues into plan analysis, lock chains, and index rollout risk.
• Overhead: both build on server-side statistics; the difference is where analysis happens – on the portal’s aggregates or on retained query-level history.

Related PostgreSQL pages

• Azure PostgreSQL Monitoring — Full guide to monitoring Flexible Server.
• PostgreSQL Query Monitoring — What query-level coverage should include.
• PostgreSQL Monitoring — Production coverage baseline for PostgreSQL.

FAQ

Should I turn off Query Store if I adopt MonPG?

No. Query Store is useful server-side instrumentation and other Azure features build on it. MonPG reads PostgreSQL’s statistics views alongside it without conflict; keep both.

QPI is free – when does paying make sense?

When the cost of not knowing exceeds the subscription: a regression that sat invisible inside a 15-minute average, an incident older than Query Store retention, or an engineer-hour burned reconstructing what a dashboard should have kept. If none of that happens to you, QPI plus discipline is a fine answer.

Does MonPG work with Azure’s VNet and private access?

Yes. The MonPG collector deploys inside your VNet and connects to Flexible Server over private networking, so the database stays unreachable from the public internet.

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.