Paessler PRTG Database Monitoring vs Percona Monitoring and Management

Paessler PRTG Database Monitoring tracks database availability, errors, and query performance across Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Azure SQL Database, AWS RDS, and ODBC/ADO-compatible databases. Its sensors measure complete-request time and query execution time separately in milliseconds. You can run custom SQL queries on a schedule and map results to monitoring channels. PRTG can flag connection timeouts, authentication failures, service interruptions, and query-validated errors; threshold alerts can go by email, SMS, push notification, syslog, or webhook.

Azure SQL Database and AWS RDS sensors collect metrics through Azure Monitor and AWS CloudWatch APIs without an agent on the database host. Scan intervals are configurable, with Paessler recommending five minutes for production monitoring. Backup checks use custom queries against backup history tables or file timestamps and require query-level setup. PRTG is offered as a Windows download or cloud-hosted service. Platforms listed include web, Windows, Android, iOS, and self-hosted deployment. A free plan covers up to 100 sensors; paid plans start at $200/mo (annual), and the free trial lasts 30 days.

Percona Monitoring and Management (PMM) is a free, open source tool for monitoring, managing, and observing databases and the servers they use. It covers MySQL, PostgreSQL, MongoDB, and deployments across on-premises, cloud, and hybrid environments. Dashboards, configuration insight, and Query Analytics support monitoring; Query Analytics ranks queries by load and provides anomaly investigation, explain plans, and customizable dashboards. Percona Advisors scan MySQL, MongoDB, and PostgreSQL databases for security gaps, misconfigurations, and performance problems, then offer recommendations. PMM includes backup and restore for MongoDB and MySQL, with scheduled or on-demand backups and point-in-time recovery. Percona Alerting is described as supporting more than 15 notification channels. Deployment options include Docker, Podman, a virtual appliance, Kubernetes or OpenShift via Helm, and an AWS Marketplace instance. PMM Server has a browser-accessible interface; its documented Docker setup recommends at least 2 CPU cores, 4 GB RAM, and 100 GB disk, and requires x86-64-v2 CPU support. PMM Client connections to the server use TLS over HTTPS.