Netdata vs Prometheus: Monitoring Compared

Two Fundamentally Different Approaches

Netdata gives you a complete monitoring dashboard the moment you start it. Prometheus gives you a metrics database that you build a monitoring system on top of. Netdata is the finished product; Prometheus is the engine.

Netdata auto-discovers running services, collects thousands of metrics per second, and displays them in real-time interactive charts — all without writing a single line of configuration. It’s designed for immediate visibility into what your server is doing right now.

Prometheus is a time-series database that scrapes metrics from exporters on a configurable schedule. It stores data efficiently for long-term retention and querying. It has no built-in dashboard — you pair it with Grafana for visualization and AlertManager for notifications.

Feature Comparison

Feature	Netdata v2.5.2	Prometheus v3.3.0
Collection method	Agent-based (push)	Pull-based (scrapes targets)
Auto-discovery	Yes — detects services automatically	No — requires manual target config
Built-in dashboard	Yes (real-time, interactive)	Basic expression browser only
Default collection interval	1 second	15 seconds (configurable)
Configuration required	Near-zero	prometheus.yml + exporter configs
Query language	Built-in filters	PromQL (powerful, steep learning curve)
Long-term storage	Tiered (RAM → disk, configurable retention)	Local TSDB (or remote write to Thanos/Mimir)
Alerting	Built-in health checks	Via AlertManager (separate component)
Notification channels	Email, Slack, Discord, PagerDuty, etc.	Via AlertManager
Metric types	Gauges, rates, automatically computed	Counters, gauges, histograms, summaries
Exporter ecosystem	Built-in collectors for 800+ integrations	100s of community exporters
Federation / clustering	Netdata Cloud (optional SaaS) or Netdata Parent	Built-in federation, or Thanos/Mimir
RAM usage	100–300 MB per node	200–500 MB (depends on cardinality)
License	GPL-3.0	Apache 2.0

Setup Comparison

Netdata — deploy and immediately get dashboards:

services:
  netdata:
    image: netdata/netdata:v2.5.2
    container_name: netdata
    hostname: my-server
    cap_add:
      - SYS_PTRACE
      - SYS_ADMIN
    security_opt:
      - apparmor:unconfined
    volumes:
      - netdata-config:/etc/netdata
      - netdata-lib:/var/lib/netdata
      - netdata-cache:/var/cache/netdata
      - /proc:/host/proc:ro
      - /sys:/host/sys:ro
      - /etc/os-release:/host/etc/os-release:ro
      - /var/run/docker.sock:/var/run/docker.sock:ro
    ports:
      - "19999:19999"
    restart: unless-stopped

volumes:
  netdata-config:
  netdata-lib:
  netdata-cache:

Start the container, open port 19999, and you have CPU, memory, disk, network, and Docker container metrics with per-second resolution. No configuration file to write.

Prometheus — requires configuration and additional components:

services:
  prometheus:
    image: prom/prometheus:v3.3.0
    container_name: prometheus
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
      - prometheus-data:/prometheus
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
      - '--storage.tsdb.retention.time=30d'
    restart: unless-stopped

  node-exporter:
    image: prom/node-exporter:v1.9.1
    container_name: node-exporter
    pid: host
    volumes:
      - /proc:/host/proc:ro
      - /sys:/host/sys:ro
      - /:/rootfs:ro
    command:
      - '--path.procfs=/host/proc'
      - '--path.sysfs=/host/sys'
      - '--path.rootfs=/rootfs'
    restart: unless-stopped

volumes:
  prometheus-data:

Plus you need prometheus.yml:

global:
  scrape_interval: 15s

scrape_configs:
  - job_name: 'node'
    static_configs:
      - targets: ['node-exporter:9100']

This gives you raw metrics in Prometheus’s expression browser. For actual dashboards, add Grafana. For alerts, add AlertManager. Each is another container and config file.

Where Each Excels

Netdata’s Strengths

• Zero-to-dashboard in 60 seconds. No exporters, no config files, no query language to learn.
• Per-second granularity. Prometheus defaults to 15-second scrapes. Netdata collects every second, which matters for catching brief spikes.
• Auto-detection. Netdata discovers MySQL, Nginx, Docker containers, and hundreds of other services without being told they exist.
• Machine learning anomaly detection. Trains on your metrics automatically and flags unusual patterns.

Prometheus’s Strengths

• PromQL. Once you learn it, PromQL is extraordinarily powerful for aggregating, filtering, and transforming metrics across dimensions. Nothing Netdata offers comes close for ad-hoc analysis.
• Scalable architecture. Prometheus with Thanos or Mimir can handle millions of time series across hundreds of servers. Netdata Parent can federate nodes, but the architecture isn’t designed for the same scale.
• Ecosystem integration. Most cloud-native tools expose a /metrics Prometheus endpoint natively. Kubernetes, Traefik, application frameworks — they all speak Prometheus.
• Custom metrics. Instrumenting your own applications with Prometheus client libraries is straightforward. Netdata focuses on system/service metrics, not custom application metrics.
• Grafana dashboards. The Prometheus + Grafana combination gives you completely custom visualization. Netdata’s dashboard is excellent but less flexible.

Resource Usage

Resource	Netdata (single server)	Prometheus + Node Exporter
Containers	1	2 (minimum), 4+ (with Grafana, AlertManager)
RAM	100–300 MB	200–500 MB (Prometheus) + 50 MB (exporter)
CPU	Low–moderate (per-second collection)	Low (15s scrape default)
Disk (per day)	~50–200 MB (compressed)	~100–500 MB (depends on cardinality)
Network	Minimal	Minimal (pull model reduces overhead)

Can You Run Both?

Yes, and many people do. Netdata even has a built-in Prometheus exporter — you can scrape Netdata’s metrics with Prometheus for long-term storage while using Netdata’s dashboard for real-time debugging. This gives you the best of both worlds: instant visibility from Netdata and historical analysis from Prometheus + Grafana.

Enable it by configuring Netdata to expose /api/v1/allmetrics?format=prometheus and adding it as a Prometheus scrape target.

Choose Netdata If…

• You want monitoring that works immediately without configuration
• Per-second metric resolution matters to you
• You’re monitoring 1–10 servers and don’t need complex cross-server queries
• You prefer a batteries-included approach over assembling components
• You don’t want to learn PromQL

Choose Prometheus If…

• You’re building a monitoring stack for 10+ servers or a Kubernetes cluster
• You need PromQL for complex metric queries and aggregations
• Your applications already expose Prometheus metrics
• Long-term metric retention (months/years) with efficient storage is a requirement
• You want full control over visualization via Grafana
• You’re instrumenting custom application metrics

FAQ

Can Netdata replace Prometheus entirely?

For small deployments (1–5 servers), yes. Netdata covers system, container, and service metrics with better granularity and zero config. For larger or Kubernetes-based deployments, Prometheus’s pull model, PromQL, and ecosystem integrations make it hard to replace.

Is PromQL hard to learn?

The basics are manageable — rate(http_requests_total[5m]) is readable once you understand the conventions. Advanced queries with aggregations, label matching, and subqueries take practice. Netdata has no equivalent learning curve.

Which uses less disk space?

Prometheus is more efficient for long-term storage due to its custom TSDB with compression. Netdata’s tiered storage is good but optimized for recent data. For 90+ day retention, Prometheus is the better choice.

Related

• How to Self-Host Netdata
• How to Self-Host Prometheus
• How to Self-Host Grafana
• Grafana vs Prometheus
• Netdata vs Beszel
• Prometheus vs Zabbix
• Best Self-Hosted Monitoring Tools