MongoDB is widely used for modern applications because it is flexible, scalable, and easy to adapt as data models change. But when MongoDB slows down, the cause is not always obvious.
A missing index, replication lag, high CPU, disk I/O pressure, or too many open connections can all create performance issues. The right MongoDB monitoring tool helps you catch these problems early and fix them before users are affected.
This guide compares the best MongoDB monitoring tools in 2026, what each tool does well, and how to choose the right one for your stack.
Key Takeaways
- MongoDB monitoring tools track query performance, connection pools, replication lag, disk I/O, and memory.
- Top tools in 2026: CubeAPM, MongoDB Atlas, SolarWinds DPM, Datadog, Prometheus + Grafana, SigNoz, New Relic, Site24x7, and Dynatrace.
- Open-source options (Prometheus + Grafana, SigNoz) cost nothing but require self-hosting.
- Atlas users: the built-in Performance Advisor and Query Profiler solve most common performance issues at no extra cost.
- Alert thresholds to set now: replication lag > 10s, memory > 85%, connections > 80%, disk > 80%.
- Match your tool to your deployment: cloud-native, self-hosted, or hybrid.
What Is MongoDB Monitoring?
MongoDB monitoring means continuously tracking the health and performance of your MongoDB instances. The main signals to watch include:
- Query execution time and slow query counts
- Connection usage and connection saturation
- Replication lag across replica set members
- Memory usage, page faults, and WiredTiger cache activity
- Disk I/O and storage utilization
- Normalized CPU usage across cores
- Index usage, query targeting, and scan-to-return ratios
A well-monitored MongoDB deployment is easier to troubleshoot, uses resources more efficiently, and gives your team early warning before small issues turn into downtime.
Key MongoDB Metrics to Monitor
These metrics are based on MongoDB’s official monitoring guidance and MongoDB Atlas documentation.
This tracks queries that return sorted results without using an index. The ideal value is 0. Any spike may point to expensive in-memory sorting, which can increase latency and memory pressure.
Query targeting compares how many documents MongoDB scans against how many documents it returns. A low scan-to-return ratio is better. A high ratio often means a query is missing the right index or scanning too much data.
Normalized CPU shows CPU usage scaled across all available cores. MongoDB says a healthy sustained range is often 40% to 70%. Below 40% may suggest overprovisioning, while above 70% may suggest underprovisioning.
Replication lag is the delay between a primary and its secondary replica set members. High lag can lead to stale reads and can make failover riskier. A threshold like 10 seconds is a common starting point, but teams should tune it based on workload and recovery requirements.
This shows how close your application is to exhausting available MongoDB connections. Sustained usage above 80% is a practical warning sign because new requests may start waiting or failing when the pool is saturated.
WiredTiger cache metrics show how efficiently MongoDB is serving data from memory instead of reading from disk. Frequent reads into cache, rising dirty bytes, or poor cache efficiency can point to memory pressure or a working set that no longer fits comfortably in RAM.
Page faults can increase during poor performance and may correlate with limited memory or large data sets. However, limited or occasional page faults do not always mean there is a problem.
The oplog window is the time range covered by the replication oplog. If a secondary is offline longer than the oplog window, it may not be able to catch up through normal replication and may require a full resync.
Quick Comparison: Top MongoDB Monitoring Tools (2026)
| Tool | Best For | Self-hosted | Pricing |
| CubeAPM | Full-stack APM + MongoDB | Yes | Predictable pricing of $0.15/GB ingested |
| MongoDB Atlas | Atlas cloud users | No | Free tier from $0/hour |
| SolarWinds Database Performance Analyzer | Enterprise database profiling | Yes | From $1,699; 14-day trial |
| Datadog | Multi-technology stacks | No | Infrastructure Pro from $15/host/month, plus add-ons |
| Prometheus + Grafana | Open-source self-hosted monitoring | Yes | Free self-hosted; Grafana Cloud has paid tiers |
| New Relic | Full-stack observability | No | Free up to 100 GB/month ingest; paid usage beyond that |
| Site24x7 | Alerting + SLA monitoring | No | Plans from $9/month; 30-day trial |
| SigNoz | OpenTelemetry-native teams | Yes | Free OSS; Cloud from $49/month |
| ManageEngine Applications Manager | On-premise enterprise monitoring | Yes | Free edition; paid plans from $395/year |
| Dynatrace | AI-driven auto-discovery | Yes, via Dynatrace Managed | Usage-based pricing; 15-day trial |
Top MongoDB Monitoring Tools (2026)
1. CubeAPM
Best for: Full-stack APM with deep MongoDB visibility
CubeAPM is a full-stack observability platform that connects MongoDB performance issues to the application requests behind them. It is useful when teams want to see slow MongoDB queries, traces, logs, infrastructure metrics, and service behavior in one place instead of checking database metrics alone.
Key Features
- End-to-end distributed tracing with MongoDB query attribution
- MongoDB dashboards for query latency, throughput, errors, and resource usage
- Alerts for replication lag, CPU, memory, and connection saturation
- Self-hosted deployment inside your infrastructure
- OpenTelemetry-native ingestion for metrics, logs, and traces
Pros
- Connects MongoDB performance directly to application traces
- Keeps telemetry inside your infrastructure
- Predictable ingest-based pricing
Cons
- Not suited for teams looking for an off-premise solution
- Strictly an observability platform and does not support cloud security management
Pricing: CubeAPM lists predictable pricing at $0.15/GB ingested.
2. MongoDB Atlas Built-In Monitoring
Best for: MongoDB Atlas users who want zero-setup database monitoring
MongoDB Atlas built-in monitoring is the simplest starting point if your MongoDB deployment already runs on Atlas. It gives you native database metrics, Performance Advisor, Query Profiler, and alerting without adding another monitoring tool.
Key Features
- Built-in cluster metrics and alerts
- Performance Advisor for index recommendations
- Query Profiler for slow query analysis
- Namespace Insights for collection-level performance
- Native Atlas integration with no extra agent setup
Pros
- No separate monitoring setup for Atlas users
- Strong database-specific visibility
- Free tier available for small Atlas workloads
Cons
- Limited to Atlas environments, so it does not fit self-hosted MongoDB
- Less useful when teams need full application, infrastructure, and trace correlation outside the MongoDB layer
Pricing: MongoDB Atlas has a Free tier at $0/hour. Paid usage depends on cluster tier, cloud provider, storage, backups, and add-ons.
3. SolarWinds Database Performance Analyzer
Best for: Enterprise database profiling across multiple database platforms
SolarWinds Database Performance Analyzer is built for database teams that need deep query and wait-time analysis. It supports cloud, on-premise, and hybrid database environments, making it a strong fit for teams monitoring MongoDB alongside other database systems.
Key Features
- Query-level performance analysis
- Wait-time analytics
- Historical database performance trends
- Cross-platform database monitoring
- Deployment support for cloud and on-premise environments
Pros
- Strong database-level troubleshooting depth
- Useful for teams managing many database platforms
- Available as a self-installed tool
Cons
- Steep learning curve
- Users find the product expensive
- Complex initial setup
Pricing: SolarWinds Database Starts at: $142 Per database / month*
4. Datadog
Best for: Teams that need MongoDB visibility across a large cloud-native stack
Datadog monitors MongoDB alongside infrastructure, APM, logs, containers, networks, and cloud services. It is best for teams already using Datadog or teams that need broad correlation across many technologies.
Key Features
- MongoDB integration with database and infrastructure metrics
- APM trace correlation
- Logs, metrics, and dashboards in one platform
- Anomaly detection and alerting
- Large integration ecosystem
Pros
- Strong cross-stack visibility
- Mature dashboards and incident workflows
- Useful for teams with many cloud services and integrations
Cons
- G2 reviewers often mention expensive pricing, especially around retention and larger environments
- The platform can feel complex because costs and features are spread across many modules
Pricing: Datadog Infrastructure Pro starts at $15/host/month when billed annually, but MongoDB monitoring costs can increase if you add APM, logs, database monitoring, synthetics, or other modules.
5. Prometheus + Grafana
Best for: Open-source teams that want full control over MongoDB monitoring
Prometheus and Grafana are a common open-source setup for MongoDB monitoring. Prometheus collects metrics through exporters, while Grafana visualizes them through dashboards. This setup works well for technical teams that are comfortable maintaining their own monitoring stack.
Key Features
- MongoDB metrics collection through exporters
- Custom dashboards in Grafana
- Prometheus Alertmanager for alerting
- Full control over storage, retention, and queries
- Large open-source community
Pros
- No software licensing cost for self-hosted Prometheus
- Highly customizable
- Strong ecosystem and community support
Cons
- G2 reviewers mention Grafana’s learning curve, especially when building advanced dashboards or setting up alerting
- Teams must maintain exporters, storage, dashboards, alerts, and upgrades themselves
Pricing: Prometheus is free and open source. Grafana Cloud has free and paid tiers, with usage-based costs depending on metrics, logs, traces, and other signals.
6. SigNoz
Best for: OpenTelemetry-native teams that want an open-source observability platform
SigNoz is an OpenTelemetry-native observability platform for traces, metrics, and logs. It is a good fit for teams that want an open-source alternative to commercial APM tools and are comfortable with OTel-based instrumentation.
Key Features
- OpenTelemetry-native traces, metrics, and logs
- Self-hosted Community Edition
- Cloud plan available
- Dashboards, alerts, and service-level visibility
- Works with OTel Collector pipelines
Pros
- Open-source and self-hostable
- Strong fit for teams standardizing on OpenTelemetry
- Cloud pricing starts lower than many enterprise APM tools
Cons
- Self-hosted deployments still require backend maintenance
- Steep learning curve
Pricing: SigNoz has a free self-hosted Community Edition. SigNoz Cloud starts at $49/month, with included usage credit and usage-based billing beyond that.
7. New Relic
Best for: Teams that want full-stack observability with a generous free tier
New Relic provides MongoDB monitoring through its infrastructure agent and connects database metrics with application performance data. It is a good fit for teams that want APM, infrastructure, logs, and custom querying in one platform.
Key Features
- MongoDB integration through New Relic infrastructure agent
- APM, infrastructure, logs, and dashboards
- NRQL for custom queries
- Alerting and workload views
- Free ingest allowance for small teams
Pros
- 100 GB/month free ingest tier
- Strong full-stack monitoring coverage
- Good fit for teams already using New Relic APM
Cons
- Can feel complex for teams that only need database monitoring
- Pricing can become harder to predict as data ingest and user seats grow
Pricing: New Relic includes 100 GB/month of free data ingest. Paid usage applies beyond the free tier.
8. Site24x7
Best for: Teams focused on alerting, uptime, SLA tracking, and simple infrastructure monitoring
Site24x7 is a cloud monitoring platform with server, application, database, network, and website monitoring. For MongoDB, it works best when the main goal is practical alerting and availability visibility rather than deep query profiling.
Key Features
- MongoDB server and performance monitoring
- Alerts and escalation policies
- SLA reporting
- Server and infrastructure monitoring
- Multi-cloud and website monitoring support
Pros
- Affordable starting plans
- Strong alerting and reporting
- Useful for SMBs and MSPs that want one broad monitoring platform
Cons
- Steep learning curve for those new to observability
- Add-ons and monitor limits need careful checking as environments grow
Pricing: Site24x7 plans start at $9/month, with add-ons and higher tiers available for larger monitoring needs.
9. ManageEngine Applications Manager
Best for: On-premise enterprises already using ManageEngine products
ManageEngine Applications Manager monitors MongoDB as part of a wider application and infrastructure monitoring setup. It is a practical fit for teams that prefer on-premise monitoring and already use ManageEngine in their IT environment.
Key Features
- On-premise deployment
- MongoDB and application monitoring
- Dependency mapping
- Performance reports and alerts
- ITSM integration with ManageEngine tools
Pros
- Good fit for on-premise and hybrid environments
- Works well for teams already in the ManageEngine ecosystem
- Free edition available
Cons
- Setup and configuration are complex, especially for larger environments
- Steeo learning curve
Pricing: ManageEngine Applications Manager has a free edition. Paid plans start at $395/year.
10. Dynatrace
Best for: Large enterprises that need AI-driven auto-discovery and root cause analysis
Dynatrace is an enterprise observability platform built around automatic discovery, OneAgent instrumentation, and Davis AI root cause analysis. It is strongest in large, dynamic environments where manual configuration becomes difficult.
Key Features
- Automatic discovery of services, infrastructure, and dependencies
- Davis AI root cause analysis
- Full-stack observability from infrastructure to user experience
- Automatic baselining
- Dynatrace Managed option for private/self-managed deployment
Pros
- Strong automation and root cause analysis
- Good fit for large enterprise environments
- Dynatrace Managed supports private deployment needs
Cons
- G2 reviewers mention a steep learning curve
- Reviews and third-party analysis often position Dynatrace as expensive or too heavy for smaller teams
Pricing: Dynatrace uses usage-based pricing. Its rate card lists Full-Stack Monitoring at $58 / moper 8 GiB host*
How to Choose the Right MongoDB Monitoring Tool
The right MongoDB monitoring tool depends on your deployment type, team size, existing stack, and budget. Start by asking one simple question: do you only need MongoDB metrics, or do you need to connect MongoDB performance to the rest of your application?
CubeAPM is the best starting point for teams that want MongoDB monitoring tied directly to application performance. It helps you connect slow queries, high latency, errors, traces, logs, and infrastructure metrics in one place. This is useful when the real problem is not only inside MongoDB, but somewhere between the database, application code, and infrastructure.
It is also a strong fit for teams that want self-hosted observability, predictable pricing, and OpenTelemetry-native monitoring without sending telemetry to a third-party SaaS backend.
Start with Atlas built-in monitoring before adding another database-only tool. Atlas gives you native database metrics, alerts, Performance Advisor, and Query Profiler for slow query analysis. This is often enough if your main concern is MongoDB health inside Atlas.
But if you need application traces, logs, infrastructure metrics, or cross-stack correlation, layer in a full-stack tool such as CubeAPM, Datadog, or New Relic.
Prometheus + Grafana is the most cost-effective option if your team can manage exporters, dashboards, alert rules, and storage. SigNoz is a strong fit if you are standardizing on OpenTelemetry and want an open-source observability platform.
ManageEngine Applications Manager fits teams that prefer on-premise monitoring, especially if they already use ManageEngine tools. For deeper database profiling and wait-time analysis, SolarWinds Database Performance Analyzer is a better fit.
Datadog is strong for teams that want MongoDB monitoring alongside cloud services, containers, infrastructure, logs, and APM. New Relic is easy to evaluate because its free tier includes 100 GB/month of data ingest.
Dynatrace is a strong choice for large, dynamic environments where automatic discovery and root-cause analysis matter, especially when manual configuration becomes hard to manage.
Built-In MongoDB Monitoring Commands
MongoDB ships with several diagnostic commands worth knowing before reaching for a third-party tool:
db.serverStatus() Returns a comprehensive snapshot of the database state including connections, memory, operation counts, and WiredTiger cache stats.
db.stats() Returns storage statistics for the current database: data size, index size, and collection count. Useful for tracking storage growth.
mongostat A command-line tool that shows a live view of operations per second, memory usage, and connections, similar to Unix vmstat.
mongotop Tracks read and write time at the collection level, helping identify which collections are consuming the most I/O.
These tools are good for immediate diagnostics but lack the historical trending, alerting, and cross-stack correlation of purpose-built solutions.
MongoDB Monitoring Best Practices
- Set alert thresholds before you need them. Do not wait for an incident to discover your baseline.
- Monitor replication lag continuously. A secondary that falls too far behind may require a full resync.
- Watch your oplog window. If it shrinks to less than a few hours, a secondary that goes offline for maintenance may not recover without a full resync.
- Review slow query logs weekly. Most MongoDB performance problems are index problems.
- Track connection pool utilization over time. Exhaustion is one of the most common causes of application-layer MongoDB errors.
- Do not ignore page faults. Frequent page faults mean your working set exceeds available memory.
Monitor Your MongoDB the Right Way
CubeAPM gives you deep visibility into MongoDB query performance, replication lag, connection pool health, and resource utilization, all in a single pane of glass. No complex setup. No hidden costs.
No credit card required. Deploy in minutes.
Disclaimer: Tool features and pricing can change over time. Always check the official vendor pages before making a final decision. Setup time and cost estimates are general ranges and may vary based on your deployment, data volume, retention needs, and infrastructure size.
Conclusion
For most teams, the decision is straightforward. If you are on Atlas, start with the built-in tools. If you run self-hosted MongoDB and want no licensing costs, Prometheus + Grafana is the most capable free option. If you need end-to-end visibility from MongoDB through to your application, CubeAPM, Datadog, or New Relic will serve you depending on your existing stack and budget.
The most important step is to start monitoring before you need it, not after an incident makes the need obvious.
FAQs
1. What is the best free MongoDB monitoring tool?
Prometheus + Grafana with the MongoDB Exporter is the most capable free option for self-hosted MongoDB. For Atlas users, the built-in Performance Advisor and Query Profiler are free and cover most use cases. SigNoz and CubeAPM both have free open-source editions.
2. What metrics should I alert on in MongoDB?
Alert on replication lag above 10 seconds, memory usage above 85%, connection saturation above 80%, and disk usage above 80%. Add slow query alerts tuned to your application SLA.
3. Is MongoDB Atlas monitoring enough?
For teams running exclusively on Atlas and focused on database-layer performance, the built-in tools cover most cases at no extra cost. If you need to correlate MongoDB performance with application traces or monitor multiple database technologies, a third-party tool adds value.