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

Grafana vs Kibana vs Zabbix

OverviewDecisionsComparisonAlternatives

Overview

Zabbix
Zabbix
Stacks684
Followers981
Votes66
GitHub Stars5.3K
Forks1.1K
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 Kibana vs Zabbix: What are the differences?

Introduction

Grafana, Kibana, and Zabbix are widely used open-source monitoring and visualization platforms. While they serve similar purposes, there are key differences between them that make each suitable for different use cases.

  1. Data Sources: Grafana provides support for a wide range of data sources including databases, messaging systems, and cloud platforms. Kibana, on the other hand, is tightly integrated with Elasticsearch and primarily focuses on analyzing logs and metrics stored in Elasticsearch. Zabbix supports multiple data sources such as SNMP, JMX, and IPMI, making it versatile for monitoring various systems.

  2. Visualization Capabilities: Grafana is renowned for its extensive and customizable visualization options. It offers a user-friendly drag-and-drop interface, allowing users to create dynamic dashboards with interactive graphs, charts, and tables. Kibana also provides visualization features, but it is more focused on log-based analysis, providing features like histograms and heat maps. Zabbix offers basic visualization capabilities but lacks the customization and interactive features of Grafana.

  3. Alerting and Notification: Grafana enables users to set up alerts based on specified conditions and receive notifications via various channels such as email, Slack, or PagerDuty. Kibana lacks built-in alerting capabilities, but it can be integrated with external systems for this purpose. Zabbix, on the other hand, has comprehensive built-in alerting capabilities, allowing users to define complex triggers and actions for alert notifications.

  4. User Interface: Grafana boasts a modern and intuitive user interface, making it easy for users to navigate and interact with their dashboards. Kibana also offers a user-friendly interface with powerful search capabilities, tailored for exploring and analyzing data in Elasticsearch. Zabbix has a more traditional and less aesthetically pleasing interface, which may require some getting used to for new users.

  5. Community and Ecosystem: Grafana has a large and active community, with extensive online resources and a marketplace to extend its functionality. Kibana also benefits from the Elasticsearch community and ecosystem, allowing for seamless integration with other Elastic Stack components. Zabbix has a dedicated user community but may have a smaller pool of available resources and integrations compared to Grafana and Kibana.

  6. Ease of Setup and Configuration: Grafana is known for its straightforward setup process and ease of configuration. It provides an intuitive web-based interface for setting up data sources, dashboards, and alerts. Kibana also offers a relatively easy setup, especially when used in combination with Elasticsearch. Zabbix, on the other hand, can be more complex to set up and configure, especially for users with limited systems administration knowledge.

In summary, Grafana excels in its wide range of data source support and powerful visualization capabilities, while Kibana is specifically designed for Elasticsearch log and metric analysis. Zabbix stands out in its comprehensive built-in alerting features and versatility in monitoring various systems. Choose Grafana for versatile and dynamic visualization, Kibana for Elasticsearch-centric analysis, and Zabbix for robust monitoring and alerting capabilities.

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Advice on Zabbix, Kibana, 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
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
vivek
vivek

Jun 8, 2020

Needs adviceonCentreonCentreonZabbixZabbixDatadogDatadog

My team is divided on using Centreon or Zabbix for enterprise monitoring and alert automation. Can someone let us know which one is better? There is one more tool called Datadog that we are using for cloud assets. Of course, Datadog presents us with huge bills. So we want to have a comparative study. Suggestions and advice are welcome. Thanks!

795k views795k
Comments

Detailed Comparison

Zabbix
Zabbix
Kibana
Kibana
Grafana
Grafana

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

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.

Smart, Highly Automated Metric Collection; Advanced Problem Detection; Intelligent Alerting and Remediation
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
5.3K
GitHub Stars
20.8K
GitHub Stars
70.7K
GitHub Forks
1.1K
GitHub Forks
8.5K
GitHub Forks
13.1K
Stacks
684
Stacks
20.6K
Stacks
18.4K
Followers
981
Followers
16.4K
Followers
14.6K
Votes
66
Votes
262
Votes
415
Pros & Cons
Pros
  • 21
    Free
  • 9
    Alerts
  • 5
    Templates
  • 5
    Service/node/network discovery
  • 4
    Base metrics from the box
Cons
  • 5
    The UI is in PHP
  • 2
    Puppet module is sluggish
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
Slack
Slack
Jira
Jira
PagerDuty
PagerDuty
Ansible
Ansible
Skype
Skype
Chef
Chef
Bugzilla
Bugzilla
HipChat
HipChat
ServiceNow.com
ServiceNow.com
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
Graphite
Graphite
InfluxDB
InfluxDB

What are some alternatives to Zabbix, 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

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.

Graphite

Graphite

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

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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