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

Kibana vs NetData

OverviewDecisionsComparisonAlternatives

Overview

Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
Netdata
Netdata
Stacks226
Followers392
Votes82

Kibana vs NetData: What are the differences?

## Key Differences between Kibana and NetData

Kibana is a data visualization and exploration tool while NetData is a real-time system monitoring and troubleshooting tool. One major difference between Kibana and NetData is their focus on different aspects of monitoring. Kibana focuses on data analysis and visualization, providing users with the ability to create interactive dashboards and in-depth reports based on the data collected. On the other hand, NetData focuses on real-time monitoring, offering users a detailed look at system metrics and performance indicators as they happen. 

Another key difference is the type of data each tool can monitor. Kibana is primarily designed for log analysis and visualization, allowing users to analyze log data from various sources and systems. In contrast, NetData focuses on system and infrastructure metrics, providing detailed insights into CPU usage, memory consumption, disk I/O, network traffic, and more. 

Additionally, the architecture of Kibana and NetData differs significantly. Kibana is typically used in conjunction with Elasticsearch, forming part of the ELK (Elasticsearch, Logstash, Kibana) stack for log analysis. On the other hand, NetData is a standalone monitoring tool that can directly collect system metrics without additional dependencies. 

Furthermore, the user interface of Kibana and NetData varies in terms of complexity and customization options. Kibana offers a highly customizable and interactive UI, allowing users to create visually appealing dashboards and reports with drag-and-drop features. In contrast, NetData provides a simple yet informative interface that focuses on presenting real-time metrics in a straightforward manner. 

Another key difference between Kibana and NetData is their scalability and deployment options. Kibana is typically used for centralized data visualization in large-scale environments, offering features for scaling horizontally and managing multiple data sources efficiently. In contrast, NetData is more suited for distributed monitoring across multiple systems and servers, providing lightweight agents that can be deployed on individual machines for real-time insights into system performance.

In summary, Kibana is a data visualization tool focused on log analysis and interactive dashboards, while NetData is a real-time monitoring tool providing detailed insights into system metrics and performance indicators as they happen.

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Advice on Kibana, Netdata

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
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

Kibana
Kibana
Netdata
Netdata

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.

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

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
Free, open-source; Easy installation and configuration; Access to monitoring unlimited metrics; Prebuilt dashboards and alarms; alerts on any metric, for a single host, an entire cluster, or your entire infrastructure; Tools for team collaboration; 800+ integrations
Statistics
GitHub Stars
20.8K
GitHub Stars
-
GitHub Forks
8.5K
GitHub Forks
-
Stacks
20.6K
Stacks
226
Followers
16.4K
Followers
392
Votes
262
Votes
82
Pros & Cons
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
  • 17
    Free
  • 14
    Easy setup
  • 12
    Graphs are interactive
  • 9
    Montiors datasbases
  • 9
    Well maintained on github
Integrations
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
Puppet Labs
Puppet Labs
CouchDB
CouchDB
ActiveMQ
ActiveMQ
Logstash
Logstash
Fail2ban
Fail2ban
TimescaleDB
TimescaleDB
Windows
Windows
Grafana
Grafana
MongoDB
MongoDB
RabbitMQ
RabbitMQ

What are some alternatives to Kibana, Netdata?

Grafana

Grafana

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.

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.

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.

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.

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