What it does
pganalyze is a PostgreSQL performance monitoring service with a collector for query and database statistics, query-plan analysis, and advisors for query, index, and vacuum tuning. The collector can run on the database host or on a separate machine that can connect to the database.
Follow a query slowdown into its plan
pganalyze is aimed at PostgreSQL teams that need database-specific evidence, not a general dashboard for every service. Its documented setup is to install the pganalyze Collector on the database host or on a reachable container or VM, configure the database connection, and enable the PostgreSQL statistics needed for collection. The Query Performance view uses pg_stat_statements data collected every minute and ranks query activity for investigation.
A practical example, not run here: if a backend endpoint becomes slow while host CPU remains normal, compare the top query groups for the affected time range, then inspect the relevant query plan and use the Query or Index Advisor to evaluate a possible change. This is a desk-research example, not a live database connection or trial.
The public Production plan is $149 per month for one database server. Scale is $399 per month for up to four servers, with additional server charges listed separately; Enterprise pricing is quote-based. This makes the cost more predictable than an unbounded ingestion meter, but server count and plan features still determine the bill.
Strengths
- Connects PostgreSQL query statistics and query-plan history to targeted tuning workflows.
- Includes query, index, and VACUUM advisors for database-specific performance investigations.
- The collector can be placed on the database host or on a separate reachable machine.
Watch out for
- The product is specific to PostgreSQL and requires a collector that can connect to the database.
- Some log-based insights depend on the database provider exporting PostgreSQL logs to the collector.
Best for
- PostgreSQL operators investigating slow queries, plan changes, index choices, and vacuum performance.
Sources
- Postgres performance at any scale | pganalyze (Oct 26, 2026)
- Get Started | pganalyze (Oct 26, 2026)
- Query Performance | pganalyze (Oct 26, 2026)
- Pricing | pganalyze (Oct 26, 2026)