10 Best Database Monitoring Tools in 2026

Your server dashboards are all green. CPU is fine, memory is fine, disk is fine — and yet checkout is timing out, a report page is spinning forever, and support tickets are piling up. Nine times out of ten, the culprit is a database quietly choking on a bad query plan, a missing index, or a lock that’s holding up half your application. Generic infrastructure monitoring won’t show you any of that, which is exactly why picking one of the best database monitoring tools for your stack matters as much as picking a good server monitor in the first place.

In this guide we’ve rounded up ten tools that actually go inside the database — tracking slow queries, connection pools, replication lag, index health, and more — across both open-source and commercial options, and across SQL and NoSQL engines. For each one we’ll tell you who it’s really built for, what it’s good at, and where it falls short, so you’re not stuck reading a vague “it depends” answer.

1. Datadog Database Monitoring

Datadog extends its broader observability platform with a dedicated Database Monitoring module that captures query samples, execution plans, and wait-event data from your databases and lines them up next to your application traces and infrastructure metrics.

Best for: teams already running Datadog for APM or infrastructure who want database context without adding another vendor.

• Query-level metrics with normalized query samples and execution plan explorer
• Out-of-the-box support for Postgres, MySQL, SQL Server, Oracle, and several managed cloud databases (RDS, Aurora, Cloud SQL)
• Automatic correlation between slow queries and the application traces that triggered them
• Host- and container-level metrics tied back to the same database instance

Limitation: it’s built as an add-on to the wider Datadog platform, so cost can climb quickly once you factor in APM, infrastructure hosts, and log ingestion alongside the database module.

2. SolarWinds Database Performance Analyzer

SolarWinds Database Performance Analyzer (DPA) is a purpose-built tool for diagnosing why queries are slow, using wait-time analysis rather than just raw resource graphs. It’s been a staple in DBA teams for years because it explains the “why,” not just the “what.”

Best for: DBAs troubleshooting recurring performance problems across a mix of on-prem and cloud database engines.

• Wait-time based root-cause analysis that pinpoints exactly what a slow query was waiting on
• Support for SQL Server, Oracle, MySQL, PostgreSQL, MongoDB, and Amazon Aurora
• Anomaly detection with historical baselines so you can tell “slow for you” from “slow, period”
• Cross-tier correlation with VM and storage metrics

Limitation: the interface feels dated next to newer SaaS tools, and licensing is per-instance, which adds up fast in large, sprawling environments.

3. Percona Monitoring and Management (PMM)

Percona Monitoring and Management is the tool we’d point most open-source-first teams toward. It’s free, self-hosted, and built on Prometheus (or VictoriaMetrics) plus Grafana, with database-specific dashboards layered on top.

Best for: teams running MySQL, MariaDB, PostgreSQL, or MongoDB who want deep query analytics without a per-node license fee.

• Query Analytics (QAN) dashboard showing the slowest and most expensive queries over time
• Native support for MySQL, PostgreSQL, MariaDB, and MongoDB in one install
• Built-in security and configuration advisors that flag risky settings
• Fully open source, so there’s no license cost tied to node count

Limitation: you own the operational burden — upgrades, storage growth, backups, and keeping PMM itself highly available all fall on your team.

4. New Relic

New Relic folds database visibility into its full-stack observability platform, giving you query performance data as part of the same trace you’d use to debug a slow API endpoint.

Best for: engineering teams that want database, application, and infrastructure telemetry in a single pane, especially if they’re already using New Relic APM.

• Automatic slow query detection surfaced directly in distributed traces
• Support for major relational databases plus common NoSQL stores like MongoDB and Redis
• Explain plan capture for supported databases to help diagnose why a query is slow
• Usage-based pricing that scales with data ingested rather than per-server licensing

Limitation: database monitoring here is a feature of a much larger platform, not a standalone specialist tool, so dedicated DBAs sometimes find it shallower than purpose-built database tools.

5. Site24x7

Site24x7 bundles database monitoring alongside server, website, and application monitoring, making it a practical option for small and mid-sized teams that don’t want to run separate tools for every layer of the stack.

Best for: smaller teams that want combined server and database monitoring in one affordable, all-in-one plan.

• Monitoring for MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, and Redis from one dashboard
• Query performance and connection/thread tracking alongside host-level metrics
• Built-in alerting via email, SMS, and common chat/incident tools
• Bundled with broader infrastructure and uptime monitoring, so you’re not paying for a separate tool per layer

Limitation: query-level diagnostics aren’t as deep as specialist tools like pganalyze or SolarWinds DPA — it’s built for breadth across your stack, not maximum depth on the database alone.

6. Zabbix

Zabbix is a long-standing open-source monitoring platform that can monitor databases through built-in templates and custom checks, on top of the server and network monitoring it’s best known for.

Best for: ops teams that already use Zabbix for infrastructure and want to extend the same tool to cover database health without adopting a second platform.

• Free and fully self-hosted, with no per-node licensing
• Community templates for MySQL, PostgreSQL, Oracle, and other common engines
• Flexible trigger and alerting engine that can combine database metrics with host-level thresholds
• Long-term metric storage and trend graphing built in

Limitation: database monitoring in Zabbix is metric-and-threshold based rather than query-level; you won’t get the deep query analytics or execution-plan tooling that specialist tools provide without significant custom scripting.

7. Prometheus + Exporters

Prometheus doesn’t monitor databases natively, but paired with exporters like mysqld_exporter, postgres_exporter, or MongoDB’s exporter, it becomes a fully open-source, highly customizable database monitoring stack — usually visualized with Grafana.

Best for: teams that already run a Prometheus/Grafana stack and want database metrics folded into the same time-series pipeline and alerting rules they use for everything else.

• Free and vendor-neutral, with a large ecosystem of community exporters for nearly every database engine
• Highly flexible PromQL queries and alerting rules tailored to your own thresholds
• Scrapes metrics on a pull model that fits well with containerized and Kubernetes-based deployments
• Pairs naturally with Grafana dashboards you may already be using for infrastructure

Limitation: there’s no built-in query analytics or root-cause diagnosis — you’re wiring together exporters, dashboards, and alert rules yourself, which takes real setup time compared to an out-of-the-box SaaS tool.

8. pganalyze

pganalyze is a specialist tool built for one job: making PostgreSQL query performance understandable. If Postgres is your primary database, this is one of the most focused tools on this list.

Best for: teams running PostgreSQL as their primary database who want deep, Postgres-specific query and index insight rather than a generic multi-database dashboard.

• Automated EXPLAIN plan collection without manually running EXPLAIN on production
• Index advisor that recommends new indexes based on real query patterns
• Schema change tracking so you can see how migrations affected query performance over time
• VACUUM and autovacuum monitoring, a common blind spot in Postgres operations

Limitation: it’s Postgres-only, so it’s not useful if your environment spans multiple database engines and you’re hoping for one tool to cover all of them.

9. Redgate SQL Monitor

Redgate SQL Monitor is aimed squarely at SQL Server (with PostgreSQL support as well), and it’s a favorite among DBA teams that need estate-wide visibility across dozens or hundreds of instances.

Best for: DBA teams managing many SQL Server instances who need alerting, historical trending, and blocking/deadlock analysis at scale.

• Deep SQL Server-specific diagnostics, including blocking chains, deadlocks, and wait statistics
• Estate-wide overview dashboards for tracking dozens of instances at once
• Customizable alerts with escalation policies suited to on-call DBA rotations
• PostgreSQL monitoring support alongside its core SQL Server focus

Limitation: its core strength is SQL Server; teams running a heavily mixed or NoSQL-heavy environment will find better multi-engine coverage elsewhere on this list.

10. Checkmk

Checkmk is an infrastructure and application monitoring platform with database plugins that extend its core host-monitoring capabilities to cover MySQL, PostgreSQL, Oracle, and MongoDB instances.

Best for: IT teams that want one monitoring platform covering networks, servers, and databases without juggling multiple tools.

• Free tier (Checkmk Raw Edition) built on open-source components
• Database-specific checks for connection counts, replication status, and table locks
• Auto-discovery of services running on monitored hosts, reducing manual setup
• Scales from a handful of servers to large, distributed environments

Limitation: like Zabbix, its database checks lean toward metrics and thresholds rather than deep query-level analysis, so specialist workloads may need a companion tool.

Comparison Table

What to look for in a database monitoring tool

Not every tool on this list solves the same problem, so before you pick one, weigh these factors against your own environment:

• Engine coverage. Make sure the tool actually supports your database engines — SQL Server, MySQL, PostgreSQL, Oracle, MongoDB, or whatever mix you run. A tool that’s excellent for Postgres won’t help you at all if half your fleet is SQL Server.
• Query-level visibility, not just host metrics. CPU and memory graphs tell you a server is busy; query analytics tell you why. Prioritize tools that show slow queries, execution plans, and locking/blocking, not just resource utilization.
• Alerting that fits your on-call process. Look for flexible thresholds, anomaly detection, and integration with the chat or paging tool your team already uses, so alerts land where people will actually see them.
• Total cost of ownership, not just license price. Open-source tools like Percona PMM, Zabbix, and Prometheus have no license fee, but someone still has to run, upgrade, and scale them. Factor in engineering time, not just the sticker price.
• How it fits your existing stack. If you already monitor servers and applications with a particular platform, a database module that plugs into that same platform will usually beat a disconnected point solution, if the depth is comparable.

FAQ

Do I need a separate database monitoring tool if I already monitor my servers?

Usually, yes. Server monitoring tells you about CPU, memory, and disk on the box the database runs on, but it can’t see inside the database engine itself — slow queries, lock contention, replication lag, and connection pool exhaustion are all invisible to host-level metrics alone.

What’s the best free database monitoring tool?

Percona Monitoring and Management is the strongest fully open-source option if you’re on MySQL, MariaDB, PostgreSQL, or MongoDB. If you want maximum flexibility and already run Prometheus and Grafana, pairing them with database exporters is another solid free route, though it takes more setup work.

Can one tool monitor both SQL and NoSQL databases?

Some can. Datadog, New Relic, Percona PMM, and Site24x7 all support a mix of relational databases alongside NoSQL stores like MongoDB or Redis. Specialist tools like pganalyze and Redgate SQL Monitor are deliberately narrower and focus on one engine or family.

Is Prometheus a good choice for database monitoring?

It can be, but only with the right exporters and dashboards set up. Prometheus itself is engine-agnostic — the actual database metrics come from exporters like mysqld_exporter or postgres_exporter. It’s a great fit if your team already runs Prometheus for infrastructure, but expect to invest setup time compared to a turnkey SaaS tool.

How is database monitoring different from database performance tuning?

Monitoring tells you what’s happening right now and what happened historically — slow queries, resource usage, error rates. Performance tuning is the follow-up work of actually fixing the problem, whether that’s adding an index, rewriting a query, or adjusting configuration. A good monitoring tool, like pganalyze or SolarWinds DPA, will point you toward the fix, but you’ll still need to apply it.

Database monitoring solves one specific problem: query and engine-level visibility. If you’re looking for a broader platform that also covers your servers, networks, and applications, see the best all-round server monitoring platforms to round out the rest of your stack.