StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Grafana vs Graphite vs Prometheus

Grafana vs Graphite vs Prometheus

OverviewDecisionsComparisonAlternatives

Overview

Graphite
Graphite
Stacks383
Followers419
Votes42
GitHub Stars6.0K
Forks1.3K
Prometheus
Prometheus
Stacks4.8K
Followers3.8K
Votes239
GitHub Stars61.1K
Forks9.9K
Grafana
Grafana
Stacks18.4K
Followers14.6K
Votes415
GitHub Stars70.7K
Forks13.1K

Grafana vs Graphite vs Prometheus: What are the differences?

Introduction

When it comes to monitoring and visualization tools, Grafana, Graphite, and Prometheus are commonly used solutions in the DevOps world. Each tool has its own strengths and weaknesses that make them suitable for different use cases.

  1. Data Storage: Grafana acts as a front end for various data sources, including Graphite and Prometheus. Graphite is primarily a time-series database that stores numeric time-series data, while Prometheus is a metrics-based monitoring system with its own time-series database. Each tool has its own data storage mechanism and querying capabilities, which can influence the choice based on specific requirements.

  2. Data Model: Graphite uses a simple tree-like data model where data is stored under predefined metrics. Prometheus, on the other hand, uses a key-value pair data model with dimensional labels for metrics. This difference in data models can impact how data is organized, queried, and visualized within each tool.

  3. Data Collection: Graphite relies on the Carbon daemon for data ingestion, while Prometheus uses its own built-in data collection service called Prometheus server. Grafana integrates with both tools to provide a unified visualization layer. The way data is collected and processed in each tool can affect real-time monitoring and alerting capabilities.

  4. Query Language: Graphite uses its own query language called Graphite Query Language (GQL) for data retrieval and manipulation. Prometheus utilizes its own query language called PromQL for querying time-series data. The differences in query languages can influence the learning curve for users and the complexity of formulating queries.

  5. Alerting and Notifications: Both Grafana and Prometheus provide alerting and notification features, allowing users to set up alerts based on specific thresholds and conditions. Grafana supports multi-channel notifications through various integrations, while Prometheus has native support for alert manager. The way alerts are configured and managed can vary between the tools.

  6. Community and Ecosystem: Grafana has a vibrant community and a rich ecosystem of plugins and dashboards, making it a popular choice for visualizing data from different sources. Graphite and Prometheus also have strong communities, but Grafana's flexibility and extensibility through plugins give it an edge when it comes to customization and integration with other tools.

In Summary, Grafana, Graphite, and Prometheus offer unique features in terms of data storage, data model, data collection, query language, alerting, and community support, making them suitable for different monitoring and visualization requirements in the DevOps landscape.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Graphite, Prometheus, Grafana

Leonardo Henrique da
Leonardo Henrique da

Pleno QA Enginneer at SolarMarket

Dec 8, 2020

Decided

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

402k views402k
Comments
Raja Subramaniam
Raja Subramaniam

Aug 27, 2019

Needs adviceonPrometheusPrometheusKubernetesKubernetesSysdigSysdig

We have Prometheus as a monitoring engine as a part of our stack which contains Kubernetes cluster, container images and other open source tools. Also, I am aware that Sysdig can be integrated with Prometheus but I really wanted to know whether Sysdig or sysdig+prometheus will make better monitoring solution.

779k views779k
Comments
StackShare
StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k
Comments

Detailed Comparison

Graphite
Graphite
Prometheus
Prometheus
Grafana
Grafana

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

carbon - a Twisted daemon that listens for time-series data;whisper - a simple database library for storing time-series data (similar in design to RRD);graphite webapp - A Django webapp that renders graphs on-demand using Cairo
Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Create, edit, save & search dashboards;Change column spans and row heights;Drag and drop panels to rearrange;Use InfluxDB or Elasticsearch as dashboard storage;Import & export dashboard (json file);Import dashboard from Graphite;Templating
Statistics
GitHub Stars
6.0K
GitHub Stars
61.1K
GitHub Stars
70.7K
GitHub Forks
1.3K
GitHub Forks
9.9K
GitHub Forks
13.1K
Stacks
383
Stacks
4.8K
Stacks
18.4K
Followers
419
Followers
3.8K
Followers
14.6K
Votes
42
Votes
239
Votes
415
Pros & Cons
Pros
  • 16
    Render any graph
  • 9
    Great functions to apply on timeseries
  • 8
    Well supported integrations
  • 6
    Includes event tracking
  • 3
    Rolling aggregation makes storage managable
Pros
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 23
    Active and responsive community
Cons
  • 12
    Just for metrics
  • 6
    Bad UI
  • 6
    Needs monitoring to access metrics endpoints
  • 4
    Not easy to configure and use
  • 3
    Supports only active agents
Pros
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
Cons
  • 1
    No interactive query builder
Integrations
Sensu
Sensu
Nagios
Nagios
Logstash
Logstash
Windows Server
Windows Server
Netdata
Netdata
Riemann
Riemann
Diamond
Diamond
Telegraf
Telegraf
collectd
collectd
Ganglia
Ganglia
No integrations available
InfluxDB
InfluxDB

What are some alternatives to Graphite, Prometheus, Grafana?

Kibana

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Nagios

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger

Jaeger, a Distributed Tracing System

Telegraf

Telegraf

It is an agent for collecting, processing, aggregating, and writing metrics. Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics.

Sysdig

Sysdig

Sysdig is open source, system-level exploration: capture system state and activity from a running Linux instance, then save, filter and analyze. Sysdig is scriptable in Lua and includes a command line interface and a powerful interactive UI, csysdig, that runs in your terminal. Think of sysdig as strace + tcpdump + htop + iftop + lsof + awesome sauce. With state of the art container visibility on top.

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

GitHub
Bitbucket

AWS CodeCommit vs Bitbucket vs GitHub

Kubernetes
Rancher

Docker Swarm vs Kubernetes vs Rancher

gulp
Grunt

Grunt vs Webpack vs gulp

Graphite
Kibana

Grafana vs Graphite vs Kibana