Few companies run a single database engine anymore. A typical stack in 2027 has PostgreSQL behind new services, MySQL or MariaDB behind older ones, SQL Server or Oracle behind the ERP, and a document store or two on top, spread across managed cloud services and self-hosted servers. Database performance monitoring tools have to follow queries across all of that and still point to the one statement, lock or missing index that is slowing an application down.
The products on this list come from three directions. Full-stack observability platforms add database views to their tracing and infrastructure data. Long-standing DBA tools have grown from one engine to many. Engine-specific specialists go deeper on PostgreSQL monitoring or MySQL monitoring than any generalist can. The right database monitoring software depends on how many engines you run and who will be looking at the dashboards. If you are also rethinking where the data lives, our comparison of Azure vs AWS vs Google Cloud covers the managed database options each cloud offers.
We built this list from vendor documentation and product pages, comparing engine coverage, slow query analysis, deployment options and licensing for each tool.
Datadog Database Monitoring (DBM) has the broadest managed-service coverage on this list. Its documentation lists Postgres on RDS, Aurora, Cloud SQL, AlloyDB, Azure, Heroku and Supabase; MySQL on RDS, Aurora, Cloud SQL and Azure; MariaDB; Oracle including RAC, Exadata and Autonomous Database; SQL Server on RDS, Azure and Cloud SQL; MongoDB and Atlas; Amazon DocumentDB; and ClickHouse.
What puts it first is how it connects database work to the rest of the system. Distributed traces, query metrics and node-level explain plans appear in one view, so a developer can move from a slow endpoint to the query behind it without switching tools. Wait event load analysis, blocking-query detection, query optimization recommendations and out-of-the-box monitors and SLO tracking come with it.
DBM is SaaS: you configure each database and install the Datadog Agent to collect data. It is billed within Datadog’s usage-based pricing, and the platform has a 14-day trial. Costs grow with every monitored host and every other Datadog product you add, so finance teams should review projected bills early.
Best for: Engineering teams already running Datadog for infrastructure and APM.
Database Performance Analyzer (DPA) is built around response time analysis. It records how long each SQL statement waits and on what, then ranks the statements that cost the most. SolarWinds features SQL Server, Azure SQL Database, Oracle, PostgreSQL and SAP HANA, and its supported list extends to MySQL, MariaDB, IBM Db2, SAP ASE and databases on Amazon RDS, EC2 and Google Cloud.
Machine learning anomaly detection learns normal behavior per database, and expert tuning advisors translate wait data into query and index recommendations. DPA can also map database performance against VMware virtual machine metrics, useful when the bottleneck sits in the hypervisor. SolarWinds says its agentless collection uses less than 1% of resources.
DPA runs in cloud or on-premises environments, is sold through subscription or volume licensing, and has a 14-day trial. It is a DBA tool more than a developer tool: it does not tie queries to application traces the way the observability platforms do.
3. Redgate Monitor — Five Engines In One Web View With Schema Deployment Markers
Redgate Monitor grew out of SQL Monitor and now covers SQL Server, PostgreSQL, Oracle, MySQL and MongoDB, on Windows or Linux servers, cloud VMs, Amazon RDS and Aurora, and Azure SQL and Flexible Server. The Global Overview pulls instances, clusters, availability groups and VMs into one view.
Query performance analysis and wait statistics are standard, and the newer Monitor AI assists with finding and tuning problem queries. Its deployment tracking stands out: changes released through Redgate’s Flyway appear on performance graphs, so you can see whether a release caused a regression. VM cost visibility, auditing reports and integrations with Splunk, ServiceNow and Octopus Deploy are included.
Monitor is available self-hosted or as fully managed SaaS. Standard is licensed per monitored server per year; Enterprise is quote-based and adds security auditing, high availability architecture and a Data API. A 14-day trial is offered. Its SQL Server depth still exceeds its coverage of the other engines, so PostgreSQL-heavy teams should trial it against a specialist.
4. Dynatrace — Database Health Scores Fed Into Davis AI Root Cause Analysis
Dynatrace treats databases as one layer of its full-stack observability platform. The Databases app monitors PostgreSQL, MySQL, SQL Server, Oracle, MariaDB and SAP HANA through Extensions Framework 2.0, with ActiveGate groups connecting to database servers remotely.
The app shows health scores and alerts per instance, size and health at the database, table and index level, and statement performance analysis with execution plans for resource-heavy queries. Blocking queries and deadlocks are detected, and Davis AI anomaly detection and root cause analysis tie a database problem to the services and users it affects. The Recommendations tab also flags auto-detected databases that are not yet monitored.
Dynatrace is sold as a usage-based subscription and offers a free trial. Setup requires network paths from ActiveGates to each database host and a monitoring user with access to system views, so plan for some firewall and permissions work. As with Datadog, it delivers the most value when the rest of the stack is on Dynatrace too.
5. New Relic — Slow Query Plans, Waits And Locks Inside The APM UI
New Relic’s database performance monitoring, branded Database 360, offers deep query analysis for MySQL, PostgreSQL and Microsoft SQL Server, and built-in integrations for Oracle, MongoDB, Azure Cosmos DB and DynamoDB.
Slow query analysis shows execution plans, wait types and locks to explain why a query is slow. Database performance sits inside the APM UI, and New Relic maps relationships between databases, application traces and infrastructure automatically. Telemetry can come from host-based agents without APM agents, which helps teams that want database visibility before instrumenting applications. Prebuilt dashboards, alerting and custom queries are included.
Pricing is usage-based. Every account includes 100 GB of data ingest per month free and unlimited Basic users, with Standard, Pro and Enterprise tiers above that. The deep analysis covers three engines, so Oracle and MongoDB users get integration metrics rather than the full slow query experience.
6. Quest Foglight — Change Tracking And Lock History Across The Widest Engine List
Foglight for Databases is Quest’s cross-platform monitoring product, and its engine list is the longest here. Quest’s Foglight Cloud documentation names SQL Server, Azure SQL Database, Oracle, Db2 for LUW, MySQL, MariaDB, PostgreSQL, Amazon Aurora, AlloyDB, MongoDB and Atlas, Amazon DocumentDB, Cassandra, SAP HANA, Redis, Redshift and Snowflake.
Foglight focuses on DBA workflows: real-time diagnostics, SQL workload analytics for problem queries, historical lock analysis, automated change tracking and adaptive baselines that alert when metrics drift from normal. Built-in advice pop-ups explain what a metric means, and drag-and-drop reporting and automated instance discovery help larger teams standardize.
Foglight runs on-premises or as Foglight Cloud SaaS. Quest does not publish pricing. The breadth comes with a heavier product to learn and administer than the SaaS observability tools above.
Precise for Databases is Idera’s multi-platform database performance tool for commercial engines: Microsoft SQL Server, Oracle Database, IBM Db2 and SAP Sybase ASE, including Amazon RDS for SQL Server and Azure SQL Database.
It samples SQL execution at least once per second with typical overhead around 1%, tracking CPU use, waits and locking, and correlates transactions with users, databases and objects. Analysts can drill down by instance, database, statement, user and program, view full blocking chains and execution plans, and read tuning recommendations. Its what-if analysis models the effect of adding or dropping indexes before anyone changes production. A performance data warehouse keeps history for trend analysis and capacity planning.
Precise is agentless and web-based, deployed on your own infrastructure, with pricing by quote and a free trial on request. It does not cover the open source engines (PostgreSQL, MySQL, MongoDB) that many newer applications use, which is why it sits behind the broader tools on this list. For enterprises running Oracle, Db2 or Sybase alongside SQL Server, it is one of the few tools that goes this deep on all four.
Percona Monitoring and Management (PMM) is an open source observability and management tool for MySQL, PostgreSQL and MongoDB. MySQL coverage includes Percona Server, Percona XtraDB Cluster, Oracle MySQL and MariaDB, and it also supports Amazon RDS and Aurora MySQL and ProxySQL.
Query Analytics ranks queries by load, flags anomalies and shows explain plans, with deeper PostgreSQL detail through the pg_stat_monitor extension. Percona Advisors run in the background to catch security gaps, misconfigurations and performance problems and explain the fix. Alerting supports more than 15 notification channels, and PMM can also run backups and restores for MySQL and MongoDB.
PMM is self-hosted across on-premises, cloud and hybrid environments, and the software itself is free. The cost is in running and maintaining it yourself; commercial support comes from Percona separately. It does not cover SQL Server or Oracle.
9. pganalyze — PostgreSQL Index Advisor With What-If Analysis And VACUUM Tuning
pganalyze is a PostgreSQL-only specialist, and its advisors go further on Postgres than any generalist. The Index Advisor detects missing indexes and recommends single- and multi-column options, testing combinations with what-if analysis. The VACUUM Advisor gives per-table autovacuum recommendations for bloat and freezing, a frequent source of Postgres slowdowns.
It collects EXPLAIN plans automatically through auto_explain and tracks them over time, reports per-query statistics with I/O versus CPU time, and detects slowdowns. Log Insights turns Postgres logs into structured data with PII filtering. It integrates with AWS, Google Cloud and Azure database services.
The hosted plans are billed per server per month, with replicas counted as half a server: Production covers one server and Scale covers up to four and adds the Query and VACUUM Advisors, query plans, Log Insights and SSO. Enterprise is an annual contract that can run on-premises in a Docker container. Free trials are available. The obvious limit is scope, since it monitors nothing other than PostgreSQL.
10. Webyog Monyog — Agentless MySQL Monitoring Over SSH With 600-Plus Best-Practice Checks
Monyog is Webyog’s MySQL monitoring tool. It covers MySQL and MariaDB, including Galera clusters, plus Amazon RDS for MySQL and MariaDB, Amazon Aurora, Azure Database for MySQL, Google Cloud SQL for MySQL and Oracle MySQL Cloud Service.
It connects over the MySQL protocol or SSH with no agents on the database servers, and tracks sessions, locks, queries, replication, long-running and locked queries and configuration changes in real time. More than 600 customizable monitors and advisors check servers against best practices, and custom dashboards show only the metrics a team cares about.
Monyog is self-hosted with a commercial license, available through Webyog’s store or sales team, and offers a 14-day trial. It is narrower than PMM in engine coverage and does not monitor PostgreSQL, so it fits teams whose estate is mostly MySQL or MariaDB and who want a commercial product with vendor support.
How To Choose A Database Performance Monitoring Tool
How Many Database Engines Do You Run?
Count engines, not just servers. For multi-database monitoring across five or more platforms, Foglight, Datadog and Database Performance Analyzer cover the most ground. If 90% of your workload is PostgreSQL or MySQL, a specialist like pganalyze, PMM or Monyog will usually give better advice for that engine than a generalist.
Who Will Use The Dashboards?
Developers chasing slow endpoints benefit from tools that link queries to application traces, which is where Datadog, Dynatrace and New Relic shine. DBAs tuning indexes and locks tend to prefer DPA, Foglight, Precise or Redgate Monitor, which present data the way a DBA works.
Are Your Databases Managed Cloud Services?
Managed services such as RDS, Aurora, Cloud SQL and Azure Database limit OS-level access, so tools must collect data through the database itself or the cloud provider’s APIs. Check each vendor’s documentation for your exact service and version rather than relying on a general “cloud supported” claim.
Do You Need Slow Query Analysis Or Just Health Metrics?
Uptime, connections and replication lag are table stakes. Slow query analysis with plans, waits and locks separates monitoring from diagnosis. If your team will act on index and query recommendations, prioritize tools with advisors and what-if modeling.
What Will It Cost At Your Scale?
Usage-based SaaS pricing is easy to start and can climb quickly with data volume and host counts. Per-server and quote-based licenses are more predictable but need upfront commitment, and open source tools trade license fees for staff time. Price the same estate with each shortlisted vendor before deciding.
Conclusion
Datadog, SolarWinds Database Performance Analyzer and Redgate Monitor top this year’s list because they combine broad engine coverage with real query-level diagnosis. Dynatrace and New Relic are strong picks for teams that live in an observability platform, while Foglight and Idera Precise for Databases serve enterprises with large commercial database estates. For open source shops, PMM, pganalyze and Monyog offer engine-specific depth at lower cost.
