Buyer’s Guide - August 2026

The 10 best MongoDB monitoring tools, ranked

Q: How do I monitor MongoDB replication lag?

From the shell, rs.status() shows member state and optime lag directly. For continuous monitoring, Netdata collects replica set state and replication lag every second with ML-assisted alerting. The Zabbix MongoDB templates include built-in replication lag triggers. Datadog Database Monitoring surfaces replication state changes and optime lag metrics alongside its query-level views.

Q: Is Datadog good for MongoDB monitoring?

Yes, particularly for query-level insight: Database Monitoring adds slow operations, explain plans and query samples on top of metrics. Be aware of two trade-offs. The default agent collection interval is 15 seconds, so it is not a per-second tool. And cost is per host plus per database host for DBM, so large fleets get expensive quickly.

MongoDB fails in database-specific ways: replication lag, oplog window shrinkage, WiredTiger cache pressure and connection saturation. This ranking grades ten tools on the metrics that actually matter for MongoDB, how fast they collect them, whether they show you the slow queries behind the graphs, and what each one costs to run at fleet scale.

Start with Netdata (free) Jump to rankings

Why this list exists

MongoDB monitoring is not general infrastructure monitoring with a database logo on it. The signals that predict an incident are MongoDB-specific: replication lag and replica set member state, the oplog window, WiredTiger cache usage and available read/write tickets, connection saturation against the available pool, and per-operation latency. A tool that polls host CPU every minute and graphs it nicely will still leave you blind to a secondary falling behind or a cache eviction storm.

Buyers make two mistakes in this category. The first is assuming a general observability platform’s default MongoDB integration matches the depth of a tool built by database people: often it collects serverStatus counters and nothing about slow operations or explain plans. The second is going the other way and adopting a MongoDB-only tool that leaves the rest of the stack unmonitored, so you end up correlating two consoles during an incident.

Three dimensions decide the outcome more than any feature checklist:

Collection granularity. Per-second collection catches the transient connection spikes and latency bursts that 15-second agent intervals and minute-level polling smooth over entirely.
Query-level insight. Metrics tell you the database is slow. Slow-query samples, profiling and explain plans tell you why. Decide whether you need the second before you buy.
Cost shape at your fleet size. Per-host, per-database-instance, per-node, per-monitor and usage-based pricing all grow differently as you add replica sets and shards.

A note on pricing: we do not quote competitor list prices in this guide. List prices for SaaS observability change often, and the number on a pricing page is rarely the number on the invoice once hosts, add-ons and data volume are counted. Instead we describe each vendor’s pricing shape and what makes the bill grow, and we link each vendor’s official pricing page so you can model your own fleet. For hands-on MongoDB runbooks, see our MongoDB guides.

We assembled the shortlist from tools practitioners actually recommend in DBA and SRE communities, cross-checked against vendor documentation for MongoDB integration depth. Every tool here has a working MongoDB integration today; we excluded anything that requires a community plugin with no maintained upstream.

The weighting reflects how these tools differ in practice. MongoDB metric depth and collection granularity carry the most weight because they determine whether you see a problem before users do. Query-level insight separates database monitoring from generic metric collection and decides whether you can fix what you find. Deployment effort, alerting quality and cost shape round out the score, with ecosystem fit as a tiebreaker.

Tester credit

Compiled by the Netdata team - Updated August 12, 2026

Sources verified

Scoring criteria

MongoDB metric depth 25%
Replication lag, oplog window, WiredTiger cache and tickets, connections, operation latency, shard and replica set state.
Collection granularity 20%
Per-second collection versus 15-second agent intervals versus minute-level polling.
Query-level insight 15%
Slow query analysis, explain plans and profiling versus metrics-only collection.
Deployment and time-to-value 15%
Agent install effort, auto-discovery, exporter assembly and ongoing maintenance.
Alerting and anomaly detection 10%
Threshold alerts, ML anomaly detection and protection against alert fatigue.
Total cost of ownership 10%
Pricing shape and how the bill grows with fleet size.
Ecosystem fit 5%
Alert channels, other databases and the surrounding infrastructure stack.

Vendor 01 / 10 · #netdata

Netdata

Real-time, per-second infrastructure monitoring with a zero-configuration open source agent and built-in machine learning, including deep MongoDB metric collection.

Best for

Teams that want MongoDB metrics at per-second granularity without configuring exporters or building dashboards
SRE and DevOps teams monitoring MongoDB alongside the rest of the infrastructure with one agent
Fleets that want unlimited metrics with predictable per-node pricing

Pricing

Per-node SaaS pricing for Netdata Cloud; Business starts at $4.50/node/month on annual plans and the per-node price decreases as node count grows
Agents are open source (AGPL) and free to run; paid plans include unlimited metrics, logs, users and retention
Free Cloud tier for small fleets

Pros

Per-second collection of MongoDB operations rate and latency, connections, memory, document counts, replica set state and replication lag
Zero-configuration auto-discovery: the agent detects MongoDB and starts collecting immediately
800+ integrations and notification channels (Slack, PagerDuty, Teams, email, webhooks) out of the box
Built-in machine learning anomaly detection with a verified 99% false-positive reduction
Customer deployments report verified 80% MTTR reduction and 90% cost reduction
Open source agent (AGPL) with 76,000+ GitHub stars and 1.5M+ downloads per day

Where teams pair it

No explain-plan or per-query profiling analysis comparable to Datadog DBM or Percona QAN; Netdata is a metrics platform, not a query tuning tool, so DBA-style query work needs a companion tool
The MongoDB collector is metrics-focused; deep sharded-cluster (mongos) coverage is thinner than ClusterControl or the Zabbix cluster template
For Atlas-only fleets, MongoDB’s built-in monitoring is free and purpose-built, so Netdata’s strongest case is self-managed MongoDB

Verdict

Netdata leads this list because it is the only tool here that combines per-second MongoDB collection, zero-configuration setup and ML-assisted alerting at a predictable per-node price with an open source agent. Replication lag, connection saturation and operation latency show up the second they happen, on the same dashboards as the host, disk and network metrics you will need during the incident anyway. The honest caveat: it answers “is MongoDB healthy and where is it slow” rather than “which query is slow and why,” so teams doing heavy query tuning will pair it with a query analytics tool. For self-managed MongoDB, nothing else gets you this much signal this fast for this little effort.

Start free -> See database monitoring ->

Vendor 02 / 10 · #datadog

Datadog

Commercial observability platform with a dedicated MongoDB Database Monitoring product that surfaces slow operations, explain plans and replication state.

Best for

Organizations already standardized on Datadog for APM and infrastructure who want MongoDB query-level insight in the same UI
Teams that need explain plans and slow-query samples without running their own profiler

Pricing

Per-host SaaS pricing for infrastructure monitoring, with Database Monitoring billed per database host on top
Usage-based add-ons (APM per host, logs per GB ingested) make the bill grow with host count and ingested volume
Free trial; no permanent free tier

Pros

MongoDB Database Monitoring surfaces slow operations, explain plans (map and list views) and replication state changes
Query Samples tab filters by database, user, client IP or application
Cluster List and Cluster Composition views show replica set health at a glance
Correlates MongoDB metrics with host CPU, memory and application traces
450+ technology integrations

Cons

Cost scales with hosts and usage; Database Monitoring adds per-database-host cost on top of infrastructure pricing
Default agent collection interval is 15 seconds, so it is not a per-second tool
Practitioners report a steep learning curve and configuration effort

Verdict

Datadog has the deepest commercial MongoDB query-level monitoring on this list: explain plans, slow operations and query samples, correlated with APM traces and host metrics in one UI. If you already pay for Datadog, adding DBM is the shortest path to query-level insight. The trade-offs are cost shape and granularity: per-host plus per-database-host pricing grows fast with fleet size, and the 15-second default collection interval misses the transient spikes per-second tools catch.

Read full Netdata vs Datadog -> Datadog pricing ->

Vendor 03 / 10 · #percona-pmm

Percona Monitoring and Management (PMM)

Open source, self-hosted database observability platform built by MongoDB specialists, with MongoDB-specific dashboards and Query Analytics.

Best for

DBAs running self-managed MongoDB who want MongoDB-specific dashboards and query analytics without SaaS cost
Teams already using Percona Server for MongoDB or Percona Backup for MongoDB

Pricing

Open source and self-hosted: you run and operate the PMM server and clients yourself
Percona sells support subscriptions and managed services on top

Pros

MongoDB dashboards for WiredTiger, MMAPv1, InMemory and RocksDB storage engines
Query Analytics (QAN) ranks MongoDB queries by load with drill-down to single queries and explain plans
Supports Percona Server for MongoDB, MongoDB Community and MongoDB Enterprise
Percona Advisors run automated checks for security gaps, misconfigurations and CVE awareness
Built-in backup and restore for MongoDB with point-in-time recovery
Open source: PMM Server AGPLv3, PMM Client Apache 2.0

Cons

Self-hosted operation burden: you maintain the PMM server, its storage and upgrades
No SaaS option; alerting and dashboards are on-prem by default
Focused on databases, so infrastructure and application monitoring outside databases needs other tools

Verdict

PMM is the strongest open source option for DBA-style MongoDB monitoring. Storage-engine-specific dashboards and Query Analytics with explain plans give it query-level depth that general metrics platforms lack, and the Advisors and backup tooling make it a genuine MongoDB operations platform. The price is operational: you run the PMM server yourself, and you will still need something else for the hosts, containers and applications around the database.

See Percona PMM -> Percona PMM overview ->

Vendor 04 / 10 · #mongodb-atlas

MongoDB Atlas

MongoDB’s own managed database platform with built-in monitoring, a real-time performance panel and performance advice for Atlas-hosted clusters.

Best for

Teams running MongoDB in Atlas who want zero-extra-tooling monitoring from the vendor
Organizations that prefer managed MongoDB and want Performance Advisor and index recommendations

Pricing

DBaaS usage-based pricing: the bill grows with cluster tier, storage, IOPS, data transfer and backups
Free tier and serverless options exist; monitoring depth scales with cluster tier

Pros

Real-Time Performance Panel shows network traffic, database operations and hardware stats at one-second granularity on M10+ clusters
Performance Advisor analyzes slow queries and recommends indexes
Namespace Insights shows collection-level query latency; Query Profiler captures slow operations
Custom alerts and historical metrics built in; integrates with Datadog, PagerDuty, Slack and others
No extra tooling to install for Atlas-hosted clusters

Cons

Only monitors Atlas-hosted clusters; it cannot monitor self-managed MongoDB
Deep monitoring features (Real-Time Performance Panel, Performance Advisor) require M10+ paid tiers
Tied to MongoDB’s own platform, so it does not unify with the rest of your infrastructure stack

Verdict

If your MongoDB runs in Atlas, the built-in monitoring is genuinely good: one-second real-time stats, index recommendations and collection-level latency from the vendor that writes the database. It ranks fourth only because it is not really an option: it monitors Atlas and nothing else. Self-managed MongoDB gets nothing from it, and even Atlas shops typically pair it with a general infrastructure monitor for everything outside the cluster.

See Atlas monitoring docs -> MongoDB pricing ->

Vendor 05 / 10 · #new-relic

New Relic

Commercial observability platform whose official MongoDB integration collects dimensional metrics from MongoDB instances, databases and collections.

Best for

Application teams that want MongoDB metrics correlated with APM traces in one platform
Organizations already on New Relic who want a supported MongoDB integration

Pricing

Usage-based SaaS: a free tier with data limits, then paid plans that scale with data ingested and user seats
The bill grows with ingested data volume and number of users

Pros

Official MongoDB integration (nri-mongodb) compatible with MongoDB 4.0+, Percona Server and Atlas M10+
Creates three entity types: MONGODB_INSTANCE, MONGODB_DATABASE and MONGODB_COLLECTION
Prometheus-based on-host integration with prebuilt dashboards and alert policies
Runs on Linux, Windows and containers

Cons

Usage-based pricing makes costs hard to predict as data volume grows
Integration is metrics-focused; query-level explain plans are not a core feature
Practitioners report outdated documentation and a learning curve

Verdict

New Relic’s official MongoDB integration is solid metrics-level monitoring with clean entity modeling down to the collection level, and it fits naturally if your application traces already live there. It does not reach the query-level depth of Datadog DBM or Percona QAN, and usage-based pricing means a chatty fleet can surprise you at invoice time. A reasonable middle option for New Relic shops; rarely the reason to adopt the platform.

Read full Netdata vs New Relic -> New Relic pricing ->

Vendor 06 / 10 · #prometheus-grafana

Prometheus + Grafana

The open source monitoring standard: Prometheus scrapes MongoDB metrics via the mongodb_exporter and Grafana visualizes and alerts on them.

Best for

Teams with Prometheus expertise who want full control over MongoDB metric collection and dashboards
Organizations that prefer open source and already run Kubernetes or Prometheus stacks

Pricing

Open source and self-hosted: you run and operate Prometheus, the exporter and Grafana yourself
Grafana Cloud offers usage-based SaaS tiers for teams that do not want to self-host

Pros

Percona’s mongodb_exporter exposes metrics from serverStatus, replSetGetStatus, collStats and indexStats
Supports MongoDB 6.0+ (Community, Enterprise, Percona Server) with multi-target scraping for sharded clusters
Grafana dashboards are highly customizable and shareable
Fully open source with no license cost

Cons

Assembly required: you configure the exporter, scrape targets, retention and alerting yourself
Scrape interval is whatever you configure (commonly 15-60s), not per-second by default
Alerting logic and long-term storage are weaker than commercial platforms; high expertise required

Verdict

Prometheus and Grafana can monitor MongoDB as deeply as anything on this list if you are willing to build it: the Percona exporter covers server status, replica set state, collection and index stats, and Grafana renders it however you want. The cost is not the license, it is the pipeline: exporter configuration, scrape tuning, retention, alerting rules and dashboard maintenance all belong to your team. The right choice when Prometheus is already your standard; a slow path otherwise.

Read full Netdata vs Grafana -> Grafana pricing ->

Vendor 07 / 10 · #clustercontrol

ClusterControl (Severalnines)

Database operations and monitoring platform from Severalnines that deploys, monitors and self-heals MongoDB replica sets and sharded clusters.

Best for

Teams running MongoDB at scale who want deployment, failover and monitoring in one platform
DBAs managing multiple database technologies (MySQL, PostgreSQL, MongoDB) from one console

Pricing

Per-node subscription billed monthly or annually, sold in node bundles
Free 30-day trial of the enterprise edition; a community edition is available

Pros

Monitors MongoDB via libmongoc with customizable dashboards and real-time alerting
Detects node or primary failures and reconfigures mongos and replica sets with self-healing workflows
Full lifecycle: deploy, scale, backup, security and query-level monitoring
Converts existing replica sets to sharded clusters by adding mongos and config servers

Cons

Commercial subscription priced per node; cost grows with cluster size
Heavier operational platform aimed at DBAs, not a lightweight per-second metrics tool
Per-metric granularity is less deep than dedicated metrics platforms

Verdict

ClusterControl is a database operations platform with monitoring built in, not a monitoring tool with database features. Its distinctive strength is acting on what it sees: automatic failover, replica set reconfiguration and sharding workflows that pure monitoring tools only alert about. If your problem is operating MongoDB clusters rather than observing them, it belongs on the shortlist. If you want per-second metric depth or a lightweight agent, look higher on this list.

See ClusterControl for MongoDB -> Severalnines pricing ->

Vendor 08 / 10 · #solarwinds-dpm

SolarWinds Database Performance Monitor

SaaS database performance monitoring with automated profiling analysis for MongoDB latency, throughput and errors.

Best for

DBAs who want a database-focused SaaS tool with automated profiling across multiple database types
Teams that want MongoDB monitoring without running their own infrastructure

Pricing

SaaS subscription priced per monitored database instance
The bill grows with the number of database instances monitored

Pros

Automated profiling analysis for MongoDB queries and structural operations
Captures nearly all serverStatus metrics plus connPoolStats via the DBO-mongo-metrics plugin
One-second resolution for query, database and infrastructure discovery data
SaaS with no self-hosted infrastructure to maintain

Cons

Per-instance pricing makes large fleets expensive
SaaS-only, so metrics leave your network
UI and pricing transparency criticized by reviewers

Verdict

SolarWinds DPM is a database-specialist SaaS with real strengths for MongoDB: automated profiling and one-second resolution put it ahead of most general platforms on query-level visibility. The constraints are commercial and architectural: per-instance pricing punishes large fleets, and SaaS-only delivery means your database metrics leave your network. A credible pick for DBA teams that want profiling without self-hosting; less so for cost-sensitive or data-residency-sensitive fleets.

Read full Netdata vs SolarWinds -> SolarWinds DPM pricing ->

Vendor 09 / 10 · #zabbix

Zabbix

Open source enterprise monitoring platform with official MongoDB templates for single nodes and sharded clusters via Zabbix Agent 2.

Best for

Enterprise IT teams already running Zabbix who want official MongoDB templates
Organizations that need MongoDB monitoring inside a broader network and infrastructure monitoring platform

Pricing

Open source and self-hosted under AGPLv3 with no license fee
Paid technical support subscriptions available from Zabbix LLC

Pros

Official ‘MongoDB node by Zabbix Agent 2’ and ‘MongoDB cluster by Zabbix Agent 2’ templates
Covers server status, replica set status, oplog stats, WiredTiger cache and tickets, connections, cursors and opcounters
Cluster template auto-discovers sharded mongod nodes and attaches node templates
Built-in triggers for replication lag, unhealthy replicas, connection and cursor thresholds
Open source AGPLv3, no license cost

Cons

Default polling intervals are coarser than per-second tools; discovery-based collection can be expensive on large clusters
Requires Zabbix Agent 2 compiled with the MongoDB plugin and manual template tuning
No query-level analysis or explain plans

Verdict

Zabbix’s official MongoDB templates are better than many assume: node and cluster coverage including oplog stats, WiredTiger tickets and replication lag triggers, with auto-discovery for sharded deployments. For enterprise IT teams already running Zabbix across the network estate, adding MongoDB this way is low-friction. The polling model is coarser than per-second tools, there is no query-level analysis, and you operate the whole platform yourself.

Read full Netdata vs Zabbix -> Zabbix pricing ->

Vendor 10 / 10 · #manageengine

ManageEngine Applications Manager

On-premises application monitoring suite with dedicated MongoDB monitoring for server stats, replica sets and cache behavior.

Best for

IT operations teams that want MongoDB monitoring inside a broader application and infrastructure monitoring suite
Organizations that prefer on-premises monitoring with scheduled polling

Pricing

Self-hosted license priced by monitor count tiers (Professional and Enterprise editions)
The bill grows with the number of monitors; add-ons priced as flat fees

Pros

Dedicated MongoDB monitoring covering server status, replica and shard statistics, replication lag and journaling
Monitors both on-premises MongoDB and MongoDB Atlas
Cache monitoring with optimum cache size analysis and threshold breach alerts
Three-level thresholds, adaptive thresholds and alert escalation to mail, SMS and Slack

Cons

Polling-based collection is not per-second; real-time visibility is limited by scheduled polls
Free edition is limited; full features require paid tiers by monitor count
Initial configuration is reported as challenging

Verdict

Applications Manager gives IT operations teams broad MongoDB coverage, including Atlas, inside a suite that also watches the rest of the application estate. The adaptive thresholds and cache size analysis are thoughtful touches. It ranks last here because its polling model is the furthest from per-second visibility and its depth is metrics-only, so it fits IT operations workflows better than SRE or DBA incident response.

Read full Netdata vs ManageEngine -> ManageEngine pricing ->

Frequently asked questions

What MongoDB metrics should I monitor?

Start with replication lag and replica set member state, since a failing secondary is often the first sign of trouble. Track operations per second and per-operation latency across reads, writes and commands. Watch connection saturation: current connections versus available connections. Monitor WiredTiger cache usage and available read/write tickets, which predict throughput collapse under load. Round it out with the oplog window, page faults, memory (resident and virtual) and disk I/O.

What is the best open source MongoDB monitoring tool?

For most teams, Netdata is the best open source MongoDB monitoring tool: per-second metrics, zero-configuration auto-discovery and ML anomaly detection with an open source (AGPL) agent. Prometheus + Grafana with Percona’s mongodb_exporter is the most flexible but you assemble the pipeline yourself. Percona PMM is the MongoDB specialist, with storage-engine dashboards and Query Analytics, self-hosted. Zabbix offers official MongoDB node and cluster templates for enterprise IT shops.

How do I monitor MongoDB Atlas?

Atlas includes built-in monitoring: the Real-Time Performance Panel shows operations and hardware stats at one-second granularity on M10+ clusters, and Performance Advisor analyzes slow queries and recommends indexes. Namespace Insights and Query Profiler give you collection-level latency and slow operation capture. You can configure custom alerts and forward them to Datadog, PagerDuty, Slack and other tools. The catch: Atlas monitoring only covers Atlas-hosted clusters, so self-managed MongoDB needs another tool.

What is the difference between mongostat, mongotop and a monitoring platform?

mongostat and mongotop show instantaneous per-second statistics on the command line, which is useful for a live look during an incident. They do not store history, send alerts or visualize trends. A monitoring platform collects MongoDB metrics continuously, stores them, alerts on thresholds or anomalies, and correlates database behavior with the rest of your stack so you can investigate after the fact, not just while it is happening.

How often should MongoDB metrics be collected?

Per-second collection, as in Netdata and the Atlas Real-Time Performance Panel, catches transient spikes in connections and latency that slower collection smooths over. Fifteen-second agent intervals (the Datadog default) and minute-level polling (Zabbix, ManageEngine) miss short-lived problems entirely. Faster collection costs more CPU and storage, so tune the interval to your incident response needs rather than collecting fast everywhere by default.

How do I monitor MongoDB replication lag?

Is Datadog good for MongoDB monitoring?

How much does MongoDB monitoring cost?

Pricing shapes vary widely: per-host (Datadog), per-node (Netdata, ClusterControl), per-instance (SolarWinds DPM), per-monitor (ManageEngine) and usage-based by ingested data (New Relic). Open source self-hosted options like the Netdata agent, Percona PMM, Prometheus + Grafana and Zabbix carry no license fee but have real operating cost in hardware and time. MongoDB Atlas includes monitoring in the cluster price for Atlas-hosted deployments. We do not quote list prices here; model your fleet against each vendor’s pricing page.

Can Netdata monitor MongoDB?

Yes. Netdata collects MongoDB operations rate and latency, connections, memory, document counts, replica set state and replication lag every second, with zero-configuration auto-discovery through its open source (AGPL) agent. Built-in ML anomaly detection carries a verified 99% false-positive reduction. What it does not provide is explain-plan or per-query profiling analysis; it is a metrics platform rather than a query tuning tool.

The 10 best MongoDB monitoring tools, ranked

How we evaluated MongoDB monitoring tools

Netdata

Datadog

Percona Monitoring and Management (PMM)

MongoDB Atlas

New Relic

Prometheus + Grafana

ClusterControl (Severalnines)

SolarWinds Database Performance Monitor

Zabbix

ManageEngine Applications Manager

Frequently asked questions

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