pgBadger vs MonPG: Post-Hoc Log Reports vs Live Monitoring

pgBadger is the standard answer for turning PostgreSQL log files into readable HTML reports – slow queries, errors, checkpoints, autovacuum, all parsed offline without ever touching the database. MonPG watches the database live. These are genuinely different jobs: one tells you what happened in last night’s logs, the other tells you what is happening right now and pages you when it matters.

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Strongest fit

• You need to know about a problem while it is happening – pgBadger reports arrive after the log is written and the report is generated.
• You want query statistics from pg_stat_statements (every execution), not only the statements that crossed log_min_duration_statement.
• You need alerting on locks, replication lag, vacuum debt, and connection saturation – log reports cannot page anyone.
• You monitor several servers and want one aggregated surface instead of per-host report files.

Not ideal when

• Your security posture forbids any tool from connecting to the database – pgBadger works entirely from log files, and that is a real, sometimes decisive advantage.
• You need deep error and log-event forensics (who, when, which error class) for an audit – that is exactly what pgBadger’s reports are built for.
• You want a free tool for occasional retrospective analysis rather than an always-on service.

Decision signals to evaluate

• Latency of insight: pgBadger is batch (run it hourly or nightly); MonPG surfaces query and lock state continuously.
• Data source: pgBadger sees only what logging captures – if log_min_duration_statement is 500ms, faster queries are invisible; MonPG reads cumulative stats for every query.
• Access model: pgBadger needs log files, no DB connection; MonPG needs a monitoring role on the database.
• Alerting: pgBadger has none; MonPG pages on regressions and saturation.
• Multi-server: pgBadger reports are per log source unless you merge logs yourself; MonPG aggregates instances natively.
• Cost: pgBadger is free open source; MonPG is a paid service – if retrospective analysis is genuinely all you need, free wins.

Related PostgreSQL pages

• PostgreSQL Slow Query Monitoring — Continuous regression detection vs log-threshold sampling.
• PostgreSQL Query Monitoring — What live query-level coverage looks like.
• PostgreSQL Monitoring — Full production coverage baseline.

FAQ

Does MonPG replace pgBadger?

Mostly, but not entirely. MonPG covers the slow-query and activity analysis continuously, with alerting. pgBadger still earns its place for deep log-event forensics and for environments where nothing is allowed to connect to the database.

pgBadger misses queries below my log threshold – does that matter?

Often, yes. A 30ms query running 50,000 times a minute can dominate your database while never appearing in a log configured at log_min_duration_statement = 500ms. pg_stat_statements-based monitoring sees cumulative cost; log-based analysis structurally cannot.

Can I run both?

Yes, and many teams do: MonPG for live monitoring and alerting, pgBadger on a nightly cron for log-level forensics. They do not conflict – one reads logs, the other reads statistics views.

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