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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.
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."
For our Predictive Analytics platform, we have used both Grafana and Kibana
- Grafana based demo video: https://www.youtube.com/watch?v=tdTB2AcU4Sg
- Kibana based reporting screenshot: https://imgur.com/vuVvZKN
Kibana has predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).
For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:
- Creating and organizing visualization panels
- Templating the panels on dashboards for repetetive tasks
- Realtime monitoring, filtering of charts based on conditions and variables
- Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
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
After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).
@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.
Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.
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.
Pros of Kibana
- Easy to setup88
- Free65
- Can search text45
- Has pie chart21
- X-axis is not restricted to timestamp13
- Easy queries and is a good way to view logs9
- Supports Plugins6
- Dev Tools4
- More "user-friendly"3
- Can build dashboards3
- Out-of-Box Dashboards/Analytics for Metrics/Heartbeat2
- Easy to drill-down2
- Up and running1
Pros of Netdata
- Free17
- Easy setup14
- Graphs are interactive12
- Montiors datasbases9
- Well maintained on github9
- Monitors nginx, redis, logs8
- Can submit metrics to Time Series databases4
- Open source3
- Easy Alert Setop2
- Netdata is also a statsd server2
- Written in C1
- GPLv31
- Zabbix0
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Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3
Cons of Netdata
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