Postgresql on Netdata

10 Best Database Monitoring Tools (2027 Comparison)

Wed, 12 Aug 2026 00:00:00 +0000

10 Best PostgreSQL Monitoring Tools for 2026

Wed, 12 Aug 2026 00:00:00 +0000

8 Best PgBouncer Monitoring Tools (2026)

Wed, 12 Aug 2026 00:00:00 +0000

Database Performance Monitoring: 14+ DBs Supported

Fri, 24 Apr 2026 00:00:00 +0000

Netdata has always collected database metrics: connections, throughput, replication lag, buffer cache hit ratios, and so on. These tell you that something is wrong, but they don’t tell you why. When your PostgreSQL response time spikes, the metric alone doesn’t tell you which query is responsible. For that, you’ve traditionally needed to SSH into the box, connect to the database, and run diagnostic queries manually. Or set up a separate database monitoring tool entirely.

Database Monitoring Software With Real-Time Visibility

Thu, 18 Dec 2025 00:00:00 +0000

Real-time database monitoring with AI-powered troubleshooting, zero configuration, and predictable costs. Monitor 15+ database platforms with per-second granularity and ML-based anomaly detection.

How to monitor and fix Database bloats in PostgreSQL?

Fri, 28 Oct 2022 00:00:00 +0000

Database bloat is disk space that was used by a table or index and is available for reuse by the database but has not been reclaimed. Bloat is created when deleting or updating tables and indexes. Here’s how to deal with it!

What is Database bloat?

Database bloat is disk space that was used by a table or index and is available for reuse by the database but has not been reclaimed. Bloat is created when deleting or updating tables and indexes.

Missing indexes in PostgreSQL? How to quickly identify it

Wed, 05 Oct 2022 00:00:00 +0000

While working on improving the Netdata PostgreSQL collector, we were monitoring our production PostgreSQL instance and something caught our attention immediately. The rows fetched ratio seemed really, really low for one particular database… there were missing indexes in PostgreSQL!

Rows fetched ratio is the percentage of rows that contain data needed to execute the query (rows fetched), out of the total number of rows scanned (rows returned). A low value indicates that the database is performing extra work by scanning a large number of rows that aren’t required to process the query.