PostgreSQL Monitoring Tools Compared (2026)

PostgreSQL gives you everything you need to understand what's happening inside your database -- pg_stat_statements, pg_stat_activity, pg_locks, EXPLAIN ANALYZE. The data is all there. The problem is turning it into actionable insight without building a custom monitoring stack.

If you're running more than a couple of PostgreSQL instances, or if "SSH in and run a query" isn't a sustainable monitoring strategy, you need a tool. Here's every major option compared.

The Baseline: What PostgreSQL Provides Natively

Before evaluating tools, know what you get for free:

-- Current activity
SELECT state, wait_event_type, wait_event, count(*)
FROM pg_stat_activity
WHERE backend_type = 'client backend'
GROUP BY state, wait_event_type, wait_event
ORDER BY count(*) DESC;

-- Top queries by total time (requires pg_stat_statements)
SELECT
    substring(query, 1, 80) AS query_preview,
    calls,
    round(total_exec_time::numeric, 1) AS total_ms,
    round(mean_exec_time::numeric, 1) AS avg_ms,
    rows
FROM pg_stat_statements
ORDER BY total_exec_time DESC
LIMIT 15;

-- Database health snapshot
SELECT
    datname,
    round(100.0 * blks_hit / nullif(blks_hit + blks_read, 0), 1) AS cache_hit_ratio,
    xact_commit AS commits,
    xact_rollback AS rollbacks,
    deadlocks
FROM pg_stat_database
WHERE datname = current_database();

If you find yourself running these queries manually more than once a week, you need a monitoring tool.

The Tool Categories

Postgres-Specialized SaaS

myDBA.dev

Purpose-built for PostgreSQL. A lightweight Go collector gathers metrics at 15-second intervals. No agent installation on the database server needed.

What it does well:

• Automated health checks across 10 domains with scored assessments
• EXPLAIN plan capture and regression detection
• Index advisor with specific recommendations
• Lock chain visualization
• Extension-specific monitoring: TimescaleDB, pgvector, PostGIS
• Replication topology mapping

Where it falls short:

• Newer product, smaller community than established tools
• No infrastructure-level metrics (CPU, memory, disk) -- monitors PostgreSQL, not the host

Pricing: Free tier (7-day retention, 1 instance). Pro tier for extended retention and multi-instance.

pganalyze

Mature PostgreSQL monitoring focused on query performance analysis. Ruby-based collector. Good documentation and established user base.

What it does well:

• Deep query performance analysis
• Automated index recommendations
• Schema evolution tracking
• Log-based EXPLAIN plan collection

Where it falls short:

• Collector requires installation on the database host or sidecar container
• Batch-interval processing (not real-time)
• No health check scoring
• No extension-specific monitoring (pgvector, PostGIS, TimescaleDB)

Pricing: Starts at $249/month per server. No free tier for production.

General-Purpose SaaS

Datadog

Monitors PostgreSQL as part of its broader platform alongside host metrics, APM, and logs.

What it does well:

• Unified view across your entire stack
• Correlate database slowness with application latency and infra issues
• Excellent alerting and dashboard customization
• APM integration shows which endpoints generate the most DB load

Where it falls short:

• Shallow Postgres depth -- no EXPLAIN plans, no index advisor, no vacuum analysis
• Query analysis relies on pg_stat_statements without deeper plan-level insights
• Postgres is one of hundreds of integrations, not the focus

Pricing: Database monitoring starts at $70/host/month (on top of $15+/host for infra monitoring).

Self-Hosted Open Source

Percona Monitoring and Management (PMM)

Open-source monitoring for PostgreSQL, MySQL, and MongoDB. Grafana-based dashboards with VictoriaMetrics storage.

What it does well:

• Free and open-source
• Query analytics (QAN) for slow query identification
• Familiar Grafana dashboards
• Multi-database support

Where it falls short:

• You must host, upgrade, backup, and scale the PMM server
• PostgreSQL support less mature than MySQL (Percona's core focus)
• No automated health checks or EXPLAIN plan regression detection
• Dashboard complexity can overwhelm smaller teams

Pricing: Free. Commercial support available.

pgwatch2

Postgres-only monitoring. Collects metrics via SQL queries, stores in InfluxDB or TimescaleDB, visualizes with Grafana.

What it does well:

• Free and Postgres-specific
• Flexible custom SQL metric collection
• Lightweight collector
• Good time-series storage choices

Where it falls short:

• Three components to host and maintain (collector, metrics store, Grafana)
• No built-in alerting (Grafana alerting or external tools)
• No EXPLAIN plan analysis or recommendations
• Significantly more setup effort than hosted tools

Pricing: Free.

CLI / Log Analysis

pgBadger

Parses PostgreSQL log files and generates detailed HTML reports. Not real-time -- post-hoc analysis only.

What it does well:

• Extremely detailed reports: query normalization, hourly patterns, error categorization
• Zero database load (reads log files, not live connections)
• Single binary, no dependencies
• Free

Where it falls short:

• Static reports, not continuous monitoring
• Requires specific PostgreSQL logging configuration
• No alerting, no dashboards, no ongoing tracking

DIY: pg_stat_statements + Grafana

Build your own by querying system views, storing results in Prometheus/InfluxDB/TimescaleDB, and building Grafana dashboards.

Strengths: Complete control, no vendor lock-in, integrates with existing Grafana.

Reality: Significant build and maintenance time. No automated analysis. Every PG upgrade may break queries. The builder must maintain it forever.

Decision Matrix

Criteria	myDBA.dev	pganalyze	Datadog	PMM	pgwatch2	pgBadger
Setup time	Minutes	Hours	Hours	Hours-Days	Hours-Days	Minutes
Self-hosting	No	No	No	Yes	Yes	N/A
Postgres depth	Deep	Deep	Shallow	Medium	Medium	Deep (logs)
EXPLAIN plans	Yes	Yes	No	No	No	No
Health check scoring	Yes	No	No	No	No	No
Index advisor	Yes	Yes	No	No	No	No
Extension monitoring	Yes	No	No	No	No	No
Real-time	Yes	Delayed	Yes	Yes	Yes	No
Alerting	Yes	Yes	Yes	Yes	Via Grafana	No
Free tier	Yes	No	No	Yes (self-host)	Yes (self-host)	Yes

How to Choose

Small team, few instances, need Postgres depth: myDBA.dev (free tier) or pganalyze (paid). Both provide the Postgres-specific insights that generic tools miss.

Platform team, many services, need unified observability: Datadog. Its Postgres monitoring is shallow but the correlation with APM and infrastructure metrics is valuable.

Budget-constrained, willing to self-host: PMM for the most features, pgwatch2 for a lighter footprint.

Just need periodic analysis: pgBadger. Parse your logs, get a report, fix the issues. No ongoing infrastructure.

The general rule: evaluate tools against your most common incidents. If your problems are missing indexes, vacuum backlogs, and replication lag, choose a tool that monitors all three with specific recommendations -- not one that shows you a CPU graph and leaves you to figure out the database-level cause.

Start Here

Regardless of which tool you choose, these are foundational:

1. Enable pg_stat_statements -- every tool relies on it
2. Set log_min_duration_statement -- capture slow queries in logs
3. Learn EXPLAIN ANALYZE -- no tool replaces understanding query plans
4. Monitor continuously -- trends reveal problems before users do

Then layer your monitoring tool on top for historical analysis, alerting, and automated recommendations.