10 Best Database Monitoring Tools And Software In 2027

Databases are central to the applications businesses rely on, but keeping them available and responsive requires more than checking whether a server is running. Slow queries, blocked sessions, connection issues, resource spikes, replication delays, and unexpected workload changes can affect application performance long before a database becomes unavailable. Without consistent monitoring, identifying the source of these problems can take considerable time.

Database monitoring tools help database administrators, developers, and IT operations teams understand how their databases behave. They collect information about database availability, query execution, CPU and memory utilization, connections, locks, and other performance indicators. Many database monitoring platforms also provide historical reporting, customizable dashboards, and alerts that notify teams when performance starts moving outside expected limits.

The available database monitoring solutions range from specialized products for SQL Server and PostgreSQL to broader observability platforms that connect database activity with application traces, infrastructure metrics, and logs. Open-source options are also available for teams that prefer to manage their own monitoring infrastructure. Some newer platforms introduce AI-assisted anomaly detection and root-cause analysis, helping teams investigate database problems without manually reviewing every metric.

Choosing the right solution depends on the database engines you use, the depth of performance information you need, and how your infrastructure is deployed. In this guide, we compare the 10 best database monitoring tools in 2027 based on database compatibility, query analysis, alerting, deployment options, observability capabilities, and open-source availability. We also examine their features, limitations, and ideal use cases to help you find the right database monitoring software for your environment.

Table of Contents

Why Do You Need Database Monitoring Tools?

Database problems can affect application response times, user experience, and business operations. A database may remain online while queries take longer to execute, connections become exhausted, or resources approach their limits. Database monitoring tools help teams identify these problems before they develop into more serious incidents.

Here are some of the main reasons organizations use database monitoring software.

Identify performance bottlenecks: Database monitoring platforms track query execution times, resource consumption, wait events, and other performance indicators. These insights help administrators identify slow queries, inefficient execution plans, blocking sessions, and resource contention. Instead of investigating every database component manually, teams can focus on the areas contributing most to performance problems.
Maintain database availability: Applications depend on databases being accessible when users need them. Monitoring tools track database availability, connection status, and service health to help teams identify interruptions. Configurable alerts can notify administrators when a database becomes unavailable or when important metrics move beyond defined thresholds.
Monitor database resources: CPU, memory, disk I/O, storage capacity, and connection utilization all affect database performance. Monitoring software provides visibility into these resources and helps teams identify unusual consumption patterns. Historical metrics can also help administrators understand whether a performance problem is temporary or part of a longer-term trend.
Detect slow queries and blocking sessions: A single inefficient query or blocked transaction can affect other database operations. Database performance monitoring tools help identify queries consuming excessive resources, sessions waiting for locks, and transactions that take longer than expected. Some products also provide execution plans and query-level recommendations to help developers investigate the underlying cause.
Reduce downtime through proactive alerts: Waiting for users to report application problems makes database troubleshooting reactive. Monitoring solutions can trigger alerts based on availability, query latency, resource usage, replication delays, and other conditions. Some platforms also use dynamic baselines to detect unusual behavior without depending entirely on manually configured thresholds.
Plan database capacity: Database workloads change as applications gain users and organizations store more information. Historical monitoring data helps administrators understand resource consumption, storage growth, and workload trends. These insights support capacity planning and help teams identify when additional resources or database optimization may be necessary.
Improve application performance visibility: Database performance is closely connected to application behavior. A slow application request may be caused by an inefficient SQL statement, a database connection problem, or infrastructure limitations. Monitoring platforms that integrate database metrics with application traces help developers and DBAs understand how database operations affect the wider application stack.
Use AI for anomaly detection and troubleshooting: Some database monitoring platforms use machine learning and AI to identify unusual performance patterns, suggest potential causes, and guide troubleshooting. These capabilities can help teams investigate incidents more efficiently, although recommendations still need to be reviewed against actual database workloads and operating conditions.

Database Monitoring Tools Comparison

The following table compares dedicated database monitoring products, database observability platforms, and an open-source monitoring solution. It highlights their database coverage, deployment models, primary use cases, and free access options.

Tool	Deployment	Database Support	Best For	Open Source	Free Plan or Trial
Redgate Monitor	Self-hosted and SaaS	SQL Server, PostgreSQL, Oracle, MySQL, MongoDB	Monitoring mixed database environments	No	14-day free trial
Datadog Database Monitoring	SaaS	PostgreSQL, MySQL, MariaDB, Oracle, SQL Server, MongoDB, ClickHouse, and more	Database and application observability	No	14-day platform trial
SolarWinds Database Performance Analyzer	Self-hosted and cloud-hosted deployment options	SQL Server, Oracle, PostgreSQL, MySQL, MariaDB, SAP HANA, and others	Query performance and wait-time analysis	No	14-day free trial
Dynatrace	SaaS and managed deployment options	MySQL, PostgreSQL, SQL Server, Oracle, Amazon RDS, Google Cloud SQL	AI-assisted database observability	No	Free trial
Percona Monitoring and Management	Self-hosted, cloud, and hybrid	MySQL, PostgreSQL, MongoDB	Open-source database monitoring	Yes	Free
ManageEngine Applications Manager	On-premises and supported cloud monitoring	Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, Redis, and more	Multi-database and infrastructure monitoring	No	30-day free trial
Site24x7	SaaS	SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, Amazon RDS, Aurora	Cloud and infrastructure database monitoring	No	30-day free trial
pganalyze	SaaS and self-hosted Enterprise Server	PostgreSQL	PostgreSQL query and performance monitoring	No	Free trial
Quest Foglight for Databases	On-premises and Foglight Cloud	SQL Server, Oracle, PostgreSQL, MySQL, DB2, MongoDB, Snowflake, and more	Enterprise database performance monitoring	No	Free trial
IBM Instana	SaaS and supported self-hosted options	PostgreSQL, MySQL, SQL Server, Oracle, and supported database services	Real-time database and application observability	No	Free trial

10 Best Database Monitoring Tools in 2027

Database monitoring tools differ in how deeply they analyze database activity and how much visibility they provide across the wider infrastructure. Some focus on query performance and database administration, while others connect database metrics with application performance monitoring and distributed tracing.

Let’s explore the best database monitoring software and platforms, including their key features, open-source availability, and G2 ratings.

#1. Redgate Monitor

Redgate Monitor is a database monitoring platform designed for database administrators and organizations managing multiple database environments. It provides a centralized view of database health and performance, helping teams identify issues across on-premises, cloud, and hybrid infrastructure. The platform supports Microsoft SQL Server, PostgreSQL, Oracle, MySQL, and MongoDB, making it useful for organizations that operate more than one database engine.

The platform collects database performance information and presents it through a web-based interface. Administrators can investigate slow queries, blocked processes, resource consumption, database availability, and other operational issues. Its alerting capabilities help teams identify potential problems before they affect applications, while historical information provides context for investigating recurring performance issues. Redgate Monitor also helps teams review database configurations, backup status, patch information, and other aspects of their database estate.

Redgate offers self-hosted and SaaS deployment options, allowing organizations to choose an arrangement that fits their infrastructure and security requirements. Its Monitor AI functionality can assist with query analysis and performance investigations, making it easier to identify potential bottlenecks. Redgate Monitor is proprietary software, and pricing is based on the monitored database environment. Its broad database support and DBA-focused diagnostics make it a strong option for organizations that need centralized database monitoring rather than a collection of separate engine-specific dashboards.

Key Features

Multi-database monitoring: Monitor SQL Server, PostgreSQL, Oracle, MySQL, and MongoDB environments through a centralized interface. This is useful for organizations managing different database technologies across on-premises and cloud infrastructure.
Real-time performance visibility: Track database health and performance metrics through dashboards that provide an overview of monitored instances, clusters, and servers.
Query performance analysis: Identify long-running queries, resource-intensive statements, and other query-related issues. Administrators can investigate performance trends and understand which database operations require attention.
Intelligent alerting: Configure alerts for performance problems, availability issues, and other database conditions. Customizable alerting helps teams respond to potential incidents before they affect applications.
Blocked process investigation: Identify blocked processes and investigate the database activity contributing to delays. This helps DBAs understand transaction contention and related performance problems.
Historical performance analysis: Review historical metrics to identify recurring issues, compare performance over time, and investigate changes following database deployments.
Database configuration monitoring: Review information about database configurations, installed versions, patches, access rights, disk usage, and backup status across supported environments.
Monitor AI: Use AI-assisted query analysis to surface performance bottlenecks and help database professionals investigate problematic queries.
Flexible deployment: Choose between self-hosted and managed SaaS deployment options, depending on infrastructure and operational requirements.

G2 Rating: 4.5/5

#2. Datadog Database Monitoring

Datadog Database Monitoring is part of the Datadog observability platform and provides detailed visibility into database performance across cloud and self-managed environments. It is designed for developers, database administrators, and platform engineering teams that need to understand how database operations affect application performance. Instead of looking at database metrics separately, teams can connect database activity with infrastructure monitoring, application performance monitoring, logs, and distributed traces.

The platform provides query-level information, including execution statistics, query performance trends, explain plans, and database resource metrics. Users can identify expensive queries, examine blocking activity, and investigate performance changes across monitored database hosts. Datadog also provides database monitoring alerts and dashboards, helping teams track query latency and other operational indicators. Its integrations make it useful for organizations that already use Datadog to monitor their application and infrastructure environments.

Datadog Database Monitoring supports PostgreSQL, MySQL, MariaDB, Oracle, SQL Server, MongoDB, Amazon DocumentDB, and ClickHouse, with support varying by deployment and database version. It is a proprietary SaaS service rather than an open-source monitoring tool. Database Monitoring is also not a standalone purchase; Datadog requires an Infrastructure Monitoring subscription. Organizations already using Datadog may find this integration useful, although the cost of adding database monitoring and other platform modules should be considered.

Key Features

Query performance monitoring: Track normalized query performance over time and identify statements that consume excessive resources or take longer than expected to execute.
Explain plan analysis: Review query execution plans to understand how database engines process statements and identify potential performance bottlenecks.
Database and application correlation: Connect database activity with application traces and infrastructure metrics to understand how database performance affects application requests.
Blocking query visibility: Investigate waiting queries and blocking activity to identify database contention and operations that may be delaying other transactions.
Multi-database support: Monitor supported self-hosted and managed database environments, including PostgreSQL, MySQL, MariaDB, Oracle, SQL Server, MongoDB, Amazon DocumentDB, and ClickHouse.
Custom dashboards: Build dashboards that combine database metrics with infrastructure, application, and log data for a broader operational view.
Database monitoring alerts: Configure alerts for slow queries, waiting queries, explain-plan cost changes, and other monitored database conditions.
AI-assisted recommendations: Use Datadog’s AI-powered root-cause analysis and query optimization recommendations to help investigate performance issues.
Infrastructure integration: Combine Database Monitoring with Datadog Infrastructure Monitoring and APM to investigate issues across the technology stack.

G2 Rating: 4.4/5

🚀 Get Your Tool Featured

Showcase your software to buyers actively comparing tools. Submit your product for editorial review and get featured on Data Stack Hub.

#3. SolarWinds Database Performance Analyzer

SolarWinds Database Performance Analyzer (DPA) is a database performance monitoring solution designed to help administrators identify and investigate database bottlenecks. It provides visibility into database response times, SQL statements, wait events, and resource utilization. The platform is particularly useful for database administrators managing SQL Server, Oracle, PostgreSQL, MySQL, MariaDB, and other supported database environments.

DPA uses response-time analysis to help teams understand where database operations spend their time. Instead of relying only on server-level CPU and memory metrics, administrators can examine database wait events and identify the queries or activities contributing to slow application responses. The platform also provides query analysis, execution-plan information, and tuning recommendations to support performance troubleshooting. Its agentless monitoring approach is intended to reduce the amount of software that needs to be installed directly on monitored database servers.

SolarWinds DPA supports database environments across on-premises and cloud infrastructure, including supported virtualized database deployments. Its monitoring capabilities help teams investigate SQL performance, blocking, deadlocks, and other database issues. It is proprietary software with a commercial licensing model and a free trial. Organizations should check the current SolarWinds product packaging, supported database versions, and licensing requirements before selecting it for a larger monitoring environment.

Key Features

Response-time analysis: Examine database response times and identify where database operations spend time waiting. This helps administrators prioritize the performance issues affecting application workloads.
Wait-time analysis: Investigate wait events to understand whether slow performance is related to CPU, storage, locking, memory, or other database resources.
SQL query analysis: Identify resource-intensive SQL statements and investigate their contribution to overall database response times.
Execution-plan visibility: Review query execution plans to understand how database engines process statements and identify opportunities for query optimization.
Database tuning advisors: Use tuning recommendations to identify potential improvements involving SQL statements and indexes.
Multi-database support: Monitor supported database systems, including SQL Server, Azure SQL, Oracle, PostgreSQL, MySQL, MariaDB, and SAP HANA.
Virtualized database monitoring: Correlate database response times with virtual machine and infrastructure metrics to investigate issues affecting database workloads running in virtualized environments.
Agentless architecture: Collect database performance information without requiring a conventional monitoring agent on every database server, subject to the product’s connection and configuration requirements.
Historical performance trends: Review performance information over time to investigate recurring bottlenecks and understand changes in database workloads.

G2 Rating: 4.5/5

#4. Dynatrace

Dynatrace is an observability platform that includes database monitoring capabilities for organizations managing complex application and infrastructure environments. It helps development, operations, and database teams understand how database activity affects application performance. Rather than treating database metrics as isolated information, Dynatrace connects database performance with application services, infrastructure, logs, and distributed traces.

Its database monitoring capabilities provide visibility into database health, query performance, resource utilization, and performance anomalies. Teams can monitor supported databases across cloud and on-premises environments and investigate how database issues affect application transactions. Dynatrace also uses its AI capabilities to identify unusual behavior and help determine the likely source of performance problems. This is useful when an application slowdown may involve several connected services and database components.

Dynatrace supports database technologies and managed services such as MySQL, PostgreSQL, Microsoft SQL Server, Oracle Database, Amazon RDS, and Google Cloud SQL. It is a proprietary platform with SaaS and supported managed deployment options. Its broad observability capabilities can be valuable for larger engineering teams, but organizations that only need basic database health monitoring may find a dedicated database monitoring tool more appropriate.

Key Features

Database fleet visibility: Monitor supported databases across cloud and on-premises environments through a centralized observability platform.
Database performance metrics: Track database health and operational indicators, including CPU, memory, I/O, and query execution times.
AI-powered root-cause analysis: Use Dynatrace’s AI capabilities to identify performance anomalies and investigate potential causes of database issues.
Slow query detection: Identify queries that contribute to database performance problems and investigate their impact on application services.
Application and database correlation: Connect database performance with application traces and service dependencies to understand how database activity affects user-facing transactions.
Cloud database monitoring: Monitor supported services such as Amazon RDS and Google Cloud SQL alongside supported self-managed database systems.
Real-time monitoring: Collect and analyze database performance information to identify issues as they develop.
Full-stack observability: Combine database metrics with infrastructure, application, and log information to investigate incidents across complex environments.
Automated problem detection: Use automatic detection and contextual insights to help teams prioritize incidents and reduce manual investigation.

G2 Rating: 4.5/5

#5. Percona Monitoring and Management (PMM)

Percona Monitoring and Management (PMM) is an open-source database monitoring and observability platform designed for MySQL, PostgreSQL, and MongoDB environments. It provides database administrators and engineering teams with a centralized interface for understanding database health, analyzing queries, and investigating performance problems. Because PMM is available as open-source software, organizations can deploy and operate the platform without purchasing a commercial monitoring license.

The platform collects database and system performance metrics and presents them through dashboards and query analytics. Administrators can review database activity, identify slow queries, investigate resource consumption, and configure alerts for important performance conditions. PMM also provides database-specific insights, allowing users to examine metrics such as MySQL InnoDB activity, MongoDB WiredTiger behavior, and PostgreSQL database statistics. These capabilities make it useful for teams that need more detailed database visibility than general infrastructure monitoring dashboards provide.

PMM can be deployed in on-premises, cloud, and hybrid environments, giving organizations control over where monitoring data is collected and stored. It also includes backup and restore capabilities for supported MySQL and MongoDB environments, alongside database configuration insights and security-related checks. Its main limitation is database coverage: it does not aim to provide the same broad commercial database support as platforms such as Redgate Monitor or Quest Foglight. For teams working with supported engines and comfortable managing their own monitoring infrastructure, PMM is a strong free database monitoring solution.

Key Features

Open-source database monitoring: Deploy PMM without purchasing a commercial monitoring license. Teams can inspect its source code, manage their own infrastructure, and adapt deployment to their operational requirements.
MySQL, PostgreSQL, and MongoDB support: Monitor supported database engines through a unified platform, with database-specific metrics and performance information.
Query Analytics: Investigate query activity and identify statements that contribute to database load. This helps administrators understand which queries need optimization.
Database-specific dashboards: Review metrics for database engines and their underlying components, including InnoDB, WiredTiger, and PostgreSQL activity.
Proactive alerting: Configure notifications for database conditions and performance issues. PMM supports integrations with multiple notification channels.
Performance and configuration insights: Review database metrics and configuration information to understand performance behavior and identify potential improvements.
Backup and restore: Use built-in backup and recovery capabilities for supported MySQL and MongoDB environments, including supported point-in-time recovery workflows.
Flexible deployment: Run PMM in on-premises, cloud, or hybrid environments using its server and client architecture.
Security checks: Use available security-related insights and checks to help identify potential configuration and operational risks.

G2 Rating: 4.6/5

#6. ManageEngine Applications Manager

ManageEngine Applications Manager is an application and infrastructure monitoring platform that includes database monitoring capabilities. It is designed for IT operations teams and database administrators who want to monitor databases alongside application servers, infrastructure, and other technology components. Its database monitoring functionality covers a broad range of relational, NoSQL, in-memory, and cloud database environments.

The platform connects to supported databases and collects performance information about resource utilization, sessions, queries, availability, and other database indicators. Administrators can use its dashboards to investigate slow SQL statements, review database health, and configure alerts when monitored values exceed defined thresholds. Applications Manager also supports application performance monitoring, which helps teams connect database activity with application response times and transaction behavior.

ManageEngine supports database environments such as Oracle, Microsoft SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, Couchbase, Memcached, and Redis, along with selected cloud database services. It is proprietary software with a 30-day free trial. Applications Manager is useful for organizations that want one monitoring console for databases and wider IT infrastructure, although teams looking for highly specialized query diagnostics may prefer a dedicated database performance monitoring product.

Key Features

Multi-database monitoring: Monitor relational databases such as Oracle, SQL Server, MySQL, and PostgreSQL, alongside supported NoSQL and in-memory systems such as MongoDB, Cassandra, Couchbase, Memcached, and Redis.
Database health monitoring: Track availability, resource utilization, sessions, and other database performance indicators through centralized dashboards.
SQL query monitoring: Monitor selected database queries and review their execution times. This helps administrators identify queries that exceed configured performance thresholds.
Wait-state analysis: Investigate database wait states and performance conditions that may be caused by locks, CPU pressure, or other resource constraints.
Intelligent alerting: Configure notifications for database performance conditions and use supported anomaly detection capabilities to identify unusual behavior.
Application performance integration: Connect database monitoring with application performance information to investigate whether delays originate in application code, network activity, or database execution.
Cloud database monitoring: Monitor supported services such as Amazon Aurora, Azure SQL Database, and Oracle Autonomous Database alongside on-premises databases.
Capacity planning: Review resource utilization trends and forecasting information to understand database growth and plan infrastructure requirements.
Agentless monitoring: Use supported JDBC and cloud API connections to collect database information without installing a separate monitoring agent on every database server.

G2 Rating: 4.7/5

⭐ Ready to Reach More Buyers?

Increase your product visibility by reaching software buyers researching the best tools. Every submission is reviewed by our editorial team.

#7. Site24x7

Site24x7 is a cloud-based monitoring platform that provides database monitoring alongside infrastructure, application, website, and network monitoring. It is designed for IT operations and DevOps teams that want to monitor the availability and performance of different technology components from one service. Its database monitoring capabilities are particularly useful for organizations managing cloud databases and hybrid infrastructure.

The platform tracks database availability, performance metrics, and important operational components. Users can monitor supported database instances, configure alerts, and review performance information through dashboards. Site24x7 also provides configuration rules that help teams manage monitoring settings across multiple database monitors. This makes it useful for organizations that want a centralized view of database health without deploying a separate monitoring platform for every database engine.

Site24x7 supports Microsoft SQL Server, MySQL, MariaDB, PostgreSQL, Oracle Database, and selected Amazon RDS and Aurora database services. It is a proprietary SaaS solution with a free trial. Although its database monitoring features are part of a wider IT monitoring platform, it may not provide the same depth of query-level diagnostics as dedicated tools such as Redgate Monitor, SolarWinds DPA, or pganalyze. It is worth considering when database monitoring needs to sit alongside broader infrastructure monitoring.

Key Features

Database availability monitoring: Track whether supported database instances are accessible and identify availability issues that may affect applications.
Multi-database support: Monitor Microsoft SQL Server, MySQL, MariaDB, PostgreSQL, Oracle Database, and selected Amazon RDS and Aurora environments.
Performance monitoring: Review database health and performance metrics to identify changes that may indicate resource or operational problems.
Proactive alerts: Configure notifications for database issues and monitored conditions so administrators can respond before problems affect users.
Database configuration rules: Apply monitoring settings and configuration rules across database monitors to reduce repetitive administrative work.
Cloud database monitoring: Monitor supported managed database services, including Amazon RDS for MySQL and PostgreSQL and Amazon Aurora MySQL and PostgreSQL.
Automated corrective actions: Use supported automation workflows to trigger corrective actions when configured monitoring conditions are met.
Centralized dashboards: Review database monitoring alongside server, application, website, and network performance information.
Reporting: Use monitoring reports to review database performance and availability trends over selected periods.

G2 Rating: 4.6/5

#8. pganalyze

pganalyze is a PostgreSQL performance monitoring and analysis platform designed for developers, database administrators, and engineering teams that rely on PostgreSQL. Unlike general-purpose database monitoring platforms, it focuses specifically on understanding PostgreSQL query performance, execution plans, logs, indexes, and database maintenance activity. This specialization makes it useful for teams that want detailed PostgreSQL insights rather than broad monitoring across unrelated database engines.

The platform collects query statistics and provides tools for investigating slow queries, wait events, locking issues, and other database performance conditions. Its query performance interface helps administrators review execution trends and identify statements that consume significant database resources. pganalyze also provides EXPLAIN plan analysis, log insights, and index recommendations to help teams understand why queries behave the way they do. Its VACUUM Advisor provides additional guidance for PostgreSQL maintenance and database health.

pganalyze is available as a managed service and through a self-hosted Enterprise Server option. It is proprietary software rather than an open-source database monitoring platform, and pricing is based on the monitored database environment. Its focus on PostgreSQL means it is not suitable for organizations that need one monitoring console for several unrelated database engines. However, for PostgreSQL-heavy applications, pganalyze provides detailed query analysis and specialized performance insights.

Key Features

PostgreSQL query monitoring: Track query statistics and performance trends to identify slow statements and workloads consuming significant database resources.
EXPLAIN plan analysis: Collect and visualize query execution plans to help developers understand how PostgreSQL executes statements and identify potential optimization opportunities.
Index Advisor: Analyze query patterns and identify potential missing or unused indexes. Recommendations help database teams investigate opportunities to improve query performance.
VACUUM Advisor: Review PostgreSQL maintenance activity and receive workload-aware insights that help teams investigate autovacuum behavior and related database issues.
Log Insights: Monitor PostgreSQL logs to identify errors, unexpected events, and other information that may indicate performance or reliability problems.
Wait-event monitoring: Investigate wait events, locking issues, and database activity to understand sources of query delays.
Automated checks and alerts: Run database checks that identify potential problems and notify administrators through supported alert destinations.
Historical performance analysis: Review query statistics and performance information over time to identify regressions and recurring workload patterns.
Flexible deployment: Use the managed pganalyze service or deploy Enterprise Server within your own infrastructure.

G2 Rating: 4.4/5

#9. Quest Foglight for Databases

Quest Foglight for Databases is an enterprise database monitoring and observability platform designed for organizations managing complex database environments. It provides a centralized view of database health, performance, and workload activity across on-premises and cloud infrastructure. The platform supports a wide range of database technologies, making it useful for IT teams that need to monitor different database engines without relying on separate monitoring products.

Foglight provides database dashboards, performance analysis, query insights, and wait-event monitoring. Its Performance Investigator helps administrators examine database workloads, identify resource bottlenecks, and investigate query behavior. The platform also uses adaptive baselines to understand normal database activity and identify deviations that may require attention. Historical performance information helps teams investigate recurring issues and understand changes in database workloads.

Quest offers Foglight through on-premises deployment and Foglight Cloud. Its database coverage includes SQL Server, Oracle, MySQL, PostgreSQL, DB2, MongoDB, Cassandra, Redis, Snowflake, and other supported platforms. Foglight is proprietary enterprise software with pricing available through the vendor. Its extensive database coverage makes it a strong choice for larger environments, although smaller teams with only one database engine may find a specialized or lighter monitoring solution easier to manage.

Key Features

Centralized database monitoring: View the health and performance of supported database environments through a common dashboard, including databases deployed on-premises and in the cloud.
Broad database support: Monitor SQL Server, Oracle, MySQL, PostgreSQL, DB2, MongoDB, Cassandra, Redis, Snowflake, and other supported database platforms.
Performance Investigator: Analyze database workloads, query activity, and performance trends to identify the issues contributing to slow database operations.
Query Insights: Identify queries that contribute to performance problems and investigate their impact across monitored database environments.
Wait-event analysis: Examine wait events at the statement level to understand whether database operations are delayed by resource contention or other bottlenecks.
Adaptive baselines: Use machine learning-based baselines to understand normal database behavior and identify unusual activity.
Historical performance analysis: Review historical database information to investigate recurring problems and understand how performance changes over time.
AI Insights: Use conversational AI capabilities to help investigate database issues, understand potential causes, and identify relevant performance information.
Cloud and on-premises deployment: Choose between supported on-premises deployment and Foglight Cloud, depending on infrastructure and operational preferences.

G2 Rating: 4.0/5

#10. IBM Instana

IBM Instana is an observability platform that provides database monitoring as part of its application and infrastructure monitoring capabilities. It is designed for engineering and operations teams that need to understand how databases affect application performance, particularly in distributed and microservices-based environments. Rather than presenting database metrics in isolation, Instana connects database activity with application traces, infrastructure information, and service dependencies.

The platform automatically discovers supported database components and collects performance information to help teams identify slow queries and potential bottlenecks. Its distributed tracing capabilities allow users to follow application requests and understand how database operations contribute to transaction latency. Instana also provides contextual insights and automated detection capabilities to help teams investigate performance problems across connected application services.

IBM Instana supports database monitoring across supported environments, including PostgreSQL, MySQL, SQL Server, Oracle, and selected managed database services. It is proprietary software and forms part of IBM’s broader observability portfolio. Its automatic discovery and application correlation capabilities make it particularly useful for teams managing microservices and distributed workloads. However, organizations that need deeper database-specific query tuning may want to compare it with specialist tools such as pganalyze, Redgate Monitor, or SolarWinds DPA.

Key Features

Automatic database discovery: Discover supported database components and collect monitoring information with less manual configuration.
Real-time database monitoring: Track database performance and availability information to identify issues as they develop.
Application dependency mapping: Visualize relationships between application services and databases to understand how database components fit into the wider application architecture.
Distributed tracing: Follow application requests across connected services and identify database operations contributing to slow transactions.
Database performance insights: Investigate database metrics and performance changes to identify potential bottlenecks affecting applications.
AI-assisted incident investigation: Use AI-enhanced observability capabilities to provide contextual information and help teams investigate potential causes of performance issues.
Automatic anomaly detection: Identify unusual behavior across monitored application and infrastructure components, including supported database environments.
Root-cause analysis: Correlate database metrics, application traces, and infrastructure information to narrow down the source of an incident.
Cloud and hybrid monitoring: Monitor supported database environments across modern application infrastructure and supported deployment models.

G2 Rating: 4.4/5

How to Choose the Best Database Monitoring Tools

The right database monitoring solution should give your team enough visibility to identify performance problems, understand their causes, and respond before they affect applications. A broad observability platform may be appropriate for a large engineering organization, while a PostgreSQL specialist or open-source monitoring solution may be a better fit for a smaller database team.

Consider the following factors when comparing database monitoring software.

Check database compatibility: Start with the database engines and versions your organization uses. Some products, such as pganalyze, focus on PostgreSQL, while platforms such as Redgate Monitor, Quest Foglight, and ManageEngine Applications Manager support several database technologies. Check support for managed cloud services and database clusters as well as self-hosted instances.
Evaluate monitoring depth: Determine whether you need basic availability and resource monitoring or detailed query-level diagnostics. Look for information about query execution times, execution plans, wait events, locks, blocking sessions, and database workload trends. Dedicated database monitoring solutions may provide deeper diagnostic information than general infrastructure monitoring tools.
Review alerting and anomaly detection: Check whether the platform supports customizable alerts, threshold-based notifications, and dynamic performance baselines. AI-assisted anomaly detection can help identify unusual behavior, but teams should understand how alerts are generated and whether thresholds can be adjusted to match their workloads.
Consider deployment requirements: Decide whether you prefer SaaS, self-hosted, on-premises, or hybrid monitoring. Cloud-based database monitoring software can reduce infrastructure maintenance, while self-hosted tools may provide greater control over monitoring data and deployment policies.
Look at application and infrastructure integration: Database performance problems often originate outside the database itself. Consider platforms that correlate database metrics with application traces, server resources, network activity, and logs. This can help teams identify whether a slowdown comes from an SQL query, an application request, or an infrastructure constraint.
Compare open-source and commercial solutions: Open-source database monitoring tools such as Percona Monitoring and Management can reduce licensing costs and provide control over deployment. Commercial platforms may offer managed services, vendor support, broader integrations, and advanced analytics. Compare the total cost of ownership, including infrastructure, storage, maintenance, and engineering effort.
Assess scalability and data retention: Consider how many database instances, hosts, clusters, and environments you need to monitor. Also review historical data retention, dashboard performance, alert volume, and licensing as your database infrastructure grows.
Evaluate AI capabilities: Some database monitoring platforms use AI to detect anomalies, explain performance problems, and recommend query improvements. Assess whether these capabilities provide actionable information for your database engines rather than relying on general AI claims.
Review pricing and support: Compare subscription models, per-host or per-instance charges, database monitoring add-ons, free trials, and support options. A platform that appears affordable for a small deployment may become more expensive when additional database instances, retention, or observability modules are added.

Explore More Top Tools

Browse expertly curated software recommendations across hundreds of business categories.

Browse Top Tools →

Conclusion

Database monitoring tools help organizations maintain database availability, identify performance bottlenecks, and understand how database activity affects their applications. The right solution depends on the database engines you use, the depth of performance analysis you need, and whether you want dedicated database monitoring or a broader observability platform.

Redgate Monitor, SolarWinds Database Performance Analyzer, and Quest Foglight for Databases are worth considering for DBA teams that need detailed performance diagnostics across database environments. Datadog, Dynatrace, and IBM Instana provide broader observability capabilities that connect database activity with application and infrastructure performance. For PostgreSQL-focused monitoring, pganalyze offers specialized query and maintenance insights, while ManageEngine Applications Manager and Site24x7 provide database monitoring alongside wider IT infrastructure visibility.

Teams looking for free database monitoring software can start with Percona Monitoring and Management. It provides open-source monitoring, query analytics, and database-specific dashboards for MySQL, PostgreSQL, and MongoDB. Before choosing a platform, compare database compatibility, monitoring depth, alerting, deployment, and total cost. A tool that helps your team identify the cause of database issues—not just report that something is wrong—will be more useful over the long term.

Tool	Best Use Case
Redgate Monitor	Monitoring mixed database environments from a centralized dashboard
Datadog Database Monitoring	Connecting database performance with application and infrastructure observability
SolarWinds Database Performance Analyzer	Query-level performance and wait-time analysis
Dynatrace	AI-assisted database and full-stack observability
Percona Monitoring and Management	Free, open-source monitoring for MySQL, PostgreSQL, and MongoDB
ManageEngine Applications Manager	Monitoring multiple database engines alongside IT infrastructure
Site24x7	Cloud database and infrastructure monitoring
pganalyze	PostgreSQL query performance and maintenance monitoring
Quest Foglight for Databases	Enterprise monitoring across diverse database environments
IBM Instana	Real-time database monitoring and application dependency tracing

FAQs

What are database monitoring tools?

Database monitoring tools are software applications that track database availability, performance, resource utilization, query execution, and operational health. They help database administrators and engineering teams identify slow queries, blocking sessions, connection problems, and other issues that may affect application performance.

What are the best database monitoring tools in 2027?

Some of the best database monitoring tools in 2027 include Redgate Monitor, Datadog Database Monitoring, SolarWinds Database Performance Analyzer, Dynatrace, Percona Monitoring and Management, ManageEngine Applications Manager, Site24x7, pganalyze, Quest Foglight, and IBM Instana. The right option depends on database compatibility, deployment requirements, and monitoring depth.

Are there free database monitoring tools?

Yes. Percona Monitoring and Management is a free, open-source database monitoring platform for MySQL, PostgreSQL, and MongoDB. Other monitoring stacks can also be built using tools such as Prometheus, Grafana, and database-specific exporters, although these require additional setup and maintenance.

What are the best open-source database monitoring tools?

Percona Monitoring and Management is one of the strongest dedicated open-source database monitoring options. It provides database-specific dashboards, query analytics, alerting, and performance insights for supported database engines. Teams can also build custom monitoring environments using Prometheus, Grafana, and database exporters.

What is the difference between database monitoring and database performance monitoring?

Database monitoring covers the overall health and operation of a database, including availability, connectivity, resource utilization, and alerts. Database performance monitoring focuses more specifically on query execution, response times, locks, wait events, resource consumption, and performance bottlenecks. Many database monitoring platforms provide both capabilities.

Which database monitoring tools support MySQL?

Several database monitoring tools support MySQL, including Redgate Monitor, Datadog Database Monitoring, SolarWinds Database Performance Analyzer, Percona Monitoring and Management, ManageEngine Applications Manager, Site24x7, and Quest Foglight. Their monitoring depth and supported MySQL deployment models vary.

Which database monitoring tools support Oracle?

Oracle Database monitoring is available through tools such as Redgate Monitor, Datadog Database Monitoring, SolarWinds Database Performance Analyzer, Dynatrace, ManageEngine Applications Manager, Quest Foglight, and IBM Instana. Organizations should verify supported Oracle versions and deployment configurations before choosing a product.

What are the best database monitoring tools for SQL Server?

Redgate Monitor, SolarWinds Database Performance Analyzer, ManageEngine Applications Manager, Quest Foglight, Datadog Database Monitoring, and Site24x7 are options for monitoring SQL Server environments. SQL Server-focused teams may prefer products with deeper query analysis, wait-event monitoring, and blocking diagnostics.

How does AI help with database monitoring?

AI can help database teams identify unusual performance patterns, detect anomalies, investigate potential root causes, and receive recommendations for query optimization. Some platforms also use machine learning to establish performance baselines and reduce unnecessary alerts. AI insights should be validated against actual database activity before taking corrective action.

What should you look for in database monitoring software?

Look for support for your database engines, query-level diagnostics, availability monitoring, resource tracking, customizable alerts, historical reporting, and application integrations. Deployment flexibility, data retention, scalability, security, pricing, and support are also important considerations when evaluating database monitoring platforms.