SQL Server monitoring spans several different data layers: query execution times, connection health, buffer cache performance, transaction log growth, and underlying server resources. Most teams end up covering these with a mix of SSMS, Performance Monitor, and cloud console views depending on where their instances run. That works until you need to correlate across them, which is exactly when it gets slow.
PRTG covers SQL Server through two main sensor approaches: SQL v2 sensors that execute queries directly against the database and return execution times or custom result values, and WMI sensors that pull server-level performance counter data from Windows without touching the database itself. Azure SQL Database has a dedicated sensor connecting via the Azure management API. Hybrid environments with instances split across on-premises and cloud work without separate configuration. Supported databases: Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Azure SQL Database, and any database accessible via ODBC or OLE DB.
SQL Server performance data tends to live in too many places at once. Query execution times in SSMS, CPU and memory in Task Manager, connection states in application logs. Matching those up when something degrades takes time, and the actual bottleneck stays unclear until you've already spent too long looking. PRTG consolidates SQL Server database metrics into a single view. Query execution times, CPU and memory utilization, active connections, and I/O wait times all sit together. When performance drops you see exactly which component is struggling, without switching between tools or manually matching timestamps across separate systems.

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SQL Server environments accumulate load gradually. Database files grow, memory fills up, disk space on log volumes tightens. Tracking those trends manually across multiple instances means periodic spot checks, and spot checks miss what happens between them. PRTG tracks resource utilization trends in real time. You get visibility into database file sizes, transaction log growth, memory buffer usage, and disk space on volumes hosting your SQL instances, before they become a problem. When metrics approach critical levels, threshold alerts fire and give you time to optimize resources before services are affected.
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Managing multiple SQL Server instances across development, staging, and production means juggling credentials, connection strings, and separate monitoring configurations. Mixed platforms like MSSQL, MySQL, and PostgreSQL make it worse. You need visibility across all of them without rebuilding your monitoring setup from scratch each time.
PRTG uses a unified sensor approach across all SQL database types. Microsoft SQL v2 sensors handle SQL Server, MySQL v2 sensors cover MySQL, and ADO SQL v2 sensors connect to any ODBC or OLE DB data source. Configure once, deploy across your environment. Also credentials are managed at the device level, so per-sensor configuration repetition is not something you deal with here.

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Application teams report "the database is slow" but system-level metrics look fine. CPU is normal. Memory is fine. The actual problem is specific queries taking too long, deadlocks blocking transactions, or availability group failovers causing brief outages. Infrastructure monitoring alone won't surface these things.
PRTG executes custom SQL statements and monitors the results. Run queries that check for blocking sessions, deadlock counts, replication lag, or slow-running stored procedures. PRTG then processes return values into individual monitoring channels, so you're not reading raw query output to find what's wrong. When application-level problems occur they show up in PRTG alongside your infrastructure metrics.
PRTG collects SQL Server performance monitoring data through several different methods, and which one applies depends on what you're monitoring. SQL v2 sensors execute queries directly against the database. WMI sensors pull performance counter data from the Windows operating system. Azure SQL Database sensors connect via Azure API for cloud databases. Here's how each approach works.
Feature | Without PRTG Without PRTG | With PRTG With PRTG |
|---|---|---|
Query Performance Tracking | Without PRTG Run queries manually in SSMS; review execution plans one at a time | With PRTG Automated query execution with real-time tracking of execution time and return values |
Multi-Database Visibility | Without PRTG Switch between SSMS connections for each database platform | With PRTG Unified dashboard for MSSQL, MySQL, PostgreSQL, Oracle, and Azure SQL |
Resource Utilization Monitoring | Without PRTG Check Task Manager, Performance Monitor, and Windows logs separately | With PRTG Consolidated view of CPU, memory, disk I/O, and database metrics in one interface |
Historical Performance Data | Without PRTG Export data manually; build custom scripts for trend analysis | With PRTG Automatic historical data collection with built-in graphs and trend visualization |
Threshold Alerting | Without PRTG Set up SQL Agent jobs or write custom scripts for alerts | With PRTG Point-and-click threshold configuration with multi-channel notifications |
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| License Name | License description | Price | License Details | Get started | Pricing Details | |
|---|---|---|---|---|---|---|
| PRTG 500 | $200 | per month paid annually | Buy nowBuy now | Enough to monitor multiple aspects of 50 devices | ||
| PRTG 1000 | $358 | per month paid annually | Buy nowBuy now | Enough to monitor multiple aspects of 100 devices | ||
| PRTG 2500 | $742 | per month paid annually | Buy nowBuy now | Enough to monitor multiple aspects of 250 devices | ||
| PRTG 5000 | $1,300 | per month paid annually | Buy nowBuy now | Enough to monitor multiple aspects of 500 devices | ||
| PRTG 10000 | $1,642 | per month paid annually | Buy nowBuy now | Enough to monitor multiple aspects of 1000 devices |
Yes. SQL v2 sensors connect via the database protocol directly, not WMI, so Linux-hosted SQL Server instances work fine. The Microsoft SQL v2 sensor executes SQL statements against them the same way it does on Windows. For operating system metrics on the Linux host itself, use SSH-based sensors or SNMP if that's enabled on the server.
No dedicated sensor exists for this, but it's doable with custom SQL statements via the Microsoft SQL v2 sensor. Query the DMVs for replica status, synchronization state, and failover readiness, then process the return values into individual channels to track each replica separately. Combine that with WMI sensors on the cluster nodes and you have reasonable availability group visibility. Not the same as a purpose-built solution, but it covers the important states.
Two options. Windows Authentication uses impersonation and inherits credentials from the object hierarchy: set them at the probe, group, or device level under Windows credentials. SQL Server Authentication uses the Database Management Systems credentials section at the device level. Either way, DBAs set credentials once and sensors inherit them. No re-entering per sensor.
Yes, with one important clarification: PRTG doesn't inspect live traffic or hook into SQL Server's query execution engine. Write a SQL query that checks for the metrics you care about, like execution counts, duration, or wait times for stored procedures and functions, then run it via the Microsoft SQL v2 sensor. The sensor measures execution time and processes return values into channels. Works well for application-specific checks, less useful if you need real-time query plan analysis.
Different data sources entirely. The SQL v2 sensor connects directly to the database and executes SQL statements. It measures query execution time and processes whatever your query returns. WMI sensors pull performance counters from Windows via WMI: buffer cache hit ratio, page life expectancy, batch requests per second, that kind of thing. SQL v2 is for query-level SQL Server performance monitoring and custom checks. WMI is for system-level SQL Server metrics. Most setups run both.
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