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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Grafana vs Graphite vs Kibana

Grafana vs Graphite vs Kibana

OverviewDecisionsComparisonAlternatives

Overview

Graphite
Graphite
Stacks383
Followers419
Votes42
GitHub Stars6.0K
Forks1.3K
Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
Grafana
Grafana
Stacks18.4K
Followers14.6K
Votes415
GitHub Stars70.7K
Forks13.1K

Grafana vs Graphite vs Kibana: What are the differences?

Introduction

Grafana, Graphite, and Kibana are popular open-source tools used for monitoring and visualizing data. While they serve similar purposes, there are significant differences between them.

  1. Storage and Data Source: Grafana is a standalone monitoring tool that can integrate with different data sources, such as Graphite, Prometheus, and Elasticsearch. Graphite, on the other hand, is a time-series database that is primarily used for storing and querying numeric time-series data. Kibana is part of the ELK stack (Elasticsearch, Logstash, and Kibana) and is primarily used for analyzing log data stored in Elasticsearch.

  2. Visualizations and Dashboards: Grafana provides a rich set of options for creating dynamic and interactive visualizations, including graphs, tables, heatmaps, and gauges. It allows users to build customizable dashboards by dragging and dropping different visual elements. Graphite, on the other hand, is more focused on graphing and charting, providing a simple interface for plotting time-series data. Kibana specializes in log data analysis and provides specific visualizations for log-based analytics, such as histograms, maps, and tag clouds.

  3. Alerting and Notifications: Grafana has built-in alerting capabilities that allow users to set up rules based on metrics and receive notifications via various channels like email, Slack, or PagerDuty. Graphite, being primarily a database, does not have native alerting features. However, third-party tools can be used to set up alerts based on Graphite metrics. Kibana offers basic alerting capabilities through its Watcher feature, which can monitor Elasticsearch data and trigger actions based on predefined conditions.

  4. Community and Ecosystem: Grafana has a large and active community, supported by a rich ecosystem of plugins and integrations. It has extensive documentation and a wide range of online resources, making it easy to find help and resources. Graphite also has an active community, but it may not have as many plugins and integrations available as Grafana. Kibana benefits from being part of the ELK stack, which has a significant user base and a range of community-driven plugins and resources.

  5. Ease of Use: Grafana is known for its user-friendly and intuitive interface, making it easy for both beginners and advanced users to create dashboards and visualizations. It has a robust query editor and provides autocomplete suggestions. Graphite has a simpler interface focused on graphing, but it may require more technical expertise to set up and configure. Kibana has a relatively steep learning curve, especially for users without prior experience with Elasticsearch and the ELK stack.

  6. Supported Use Cases: Grafana is widely used for monitoring and visualization in various domains, including infrastructure monitoring, application performance monitoring, and business intelligence. It is versatile and can integrate with multiple data sources, making it suitable for different use cases. Graphite is mainly used for time-series data storage and graphing, making it suitable for scenarios where historical trend analysis is critical. Kibana is primarily used for log analysis and enables users to search, analyze, and visualize log data in real-time.

In summary, Grafana is a versatile monitoring and visualization tool with a user-friendly interface, supporting various data sources and use cases. Graphite is focused on time-series data storage and graphing, while Kibana specializes in log analysis within the ELK stack environment.

Why do developers choose Kibana vs Grafana vs Graphite?

  • Grafana is a general purpose dashboard tool that integrates with many data sources, including Graphite, InfluxDB, and OpenTSDB. Fans of Grafana call it beautiful and easy to use, and love its many integrations.
  • Kibana is loved by fans of Elasticsearch; as part of the Elastic Stack it integrates seamlessly with other Elastic products. Fans also cite its ease of setup, pie chart capability, and user-friendliness as pros.
  • Fans of Graphite appreciate its storage functions, integrations (including Grafana), and ability to render any graph.

What are some alternatives to Grafana, Kibana, and Graphite?

  • Prometheus - An open-source service monitoring system and time series database, developed by SoundCloud
  • Nagios - Complete monitoring and alerting for servers, switches, applications, and services
  • StatsD - Simple daemon for easy stats aggregation
  • Sensu - Open source monitoring framework

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Advice on Graphite, Kibana, Grafana

Matt
Matt

Senior Software Engineering Manager at PayIt

May 3, 2021

DecidedonGrafanaGrafanaPrometheusPrometheusKubernetesKubernetes

Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

1.1M views1.1M
Comments
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
matteo1989it
matteo1989it

Jun 26, 2019

ReviewonKibanaKibanaGrafanaGrafanaElasticsearchElasticsearch

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

757k views757k
Comments

Detailed Comparison

Graphite
Graphite
Kibana
Kibana
Grafana
Grafana

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

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.

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
Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards
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
20.8K
GitHub Stars
70.7K
GitHub Forks
1.3K
GitHub Forks
8.5K
GitHub Forks
13.1K
Stacks
383
Stacks
20.6K
Stacks
18.4K
Followers
419
Followers
16.4K
Followers
14.6K
Votes
42
Votes
262
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
  • 88
    Easy to setup
  • 65
    Free
  • 45
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
Cons
  • 7
    Unintuituve
  • 4
    Elasticsearch is huge
  • 4
    Works on top of elastic only
  • 3
    Hardweight UI
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
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
InfluxDB
InfluxDB

What are some alternatives to Graphite, Kibana, Grafana?

Prometheus

Prometheus

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.

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.

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