Graylog vs Kibana

Management tools are used when the work is to be organized and for the coordination of the teams. With the help of these kinds of tools, the person can complete any task faster. Also, they can track projects, manages the team, and plan for future tasks. If any device fails to work, what does a field engineer do? The answer is simple, he checks out the log files and with the right application to handle the tasks, it becomes easy to seek out the problem in the device. Both Graylog and Kibana are log management software that tries to automate the majority of log management tasks. There are various aspects in which Graylog and Kibana differ. Let us discuss that.

What is Graylog?

Graylog is written in Java language. It works with GELF, which stands for Graylog extended log format, and the search language it uses is Lucene syntax. It depends on MongoDB and Elasticsearch and is termed a powerful log management solution. Graylog is made up of MongoDB, Graylog’s web interface, and Graylog’s main server. Various different config files are exchanged and Content Packs with other users as it has a community marketplace.

Key Features

1. It has the features of a log collector and consolidator.
2. This tool is helpful in creating and managing log files.
3. It also acts as a data viewer.

Advantages

1. It has a User-friendly interface.
2. A variety of data formats can be handled with Graylog.
3. It is quite flexible regarding the authentication process and user permissions.
4. It can send you email alerts.
5. It uses simple widgets to create custom reports, dashboards, and monitors.

Disadvantages

1. It cannot read Syslog files.
2. This tool’s dashboard is not user-friendly.
3. It is not suitable for work in large organizations.

What is Kibana?

Kibana is a part of the ELK stack. It is one of the open-source virtualization tools and is used for time-series analysis, log analysis, and application monitoring. It offers a tool named Canvas. In this Kibana tool, anyone can create slide decks that extract real-time data directly from Elasticsearch. The customers can easily visualize their Elasticsearch data and navigate the Elastic Stack. And real-time data can be seen through the help of various charts, tables, maps, and with many other tools present in Kibana.

Key Features

1. Using the Kibana lens, the drag-and-drop experience is simplified in data visualization.
2. The Time Series Visual Builder (TSVB) is a framework that is used to combine an infinite number of aggregations and pipeline aggregations to display complex data.
3. In this Kibana tool, community-driven plugin modules add more functionality.

Advantages

1. It is an open-source and free-to-use tool.
2. Its setup is quite easy and simple for a beginner to understand.
3. It is highly interactive.
4. Canvas visualization is used for analyzing complex data in an easy way.

Disadvantages

1. It has security issues.
2. It is quite slow and the plugin add-ons are also a difficult task.
3. Debugging option is not available.

Difference between Graylog and Kibana:

	Graylog	Kibana
Dependent	It depends on MongoDB and Elasticsearch to operate.	It is one of the elements of the ELK stack.
Learning Curve	It has a Flat learning curve.	It has a Steep learning curve as the ELK stack is an advanced suite of products.
Usability	It solves simple programs.	It solves complex problems.
Maintenance	Less effort is needed in the maintenance.	It is difficult in terms of maintenance.
Plugins	It has Limited plugins.	There are a lot of plugins present because of the different levels of complex solving capabilities that the ELK stack brings.
Pricing	A fixed price for the enterprise edition is $1500.	It is free to use.
Visualizations	The visualizations are dependent on Grafana.	It has in-built visualizations.
Indexing	It has no control over indexing.	It has total control over the indexing of data as it provides flexibility.

Conclusion

Graylog and Kibana are the two most used and popular log management solutions. It shares a lot of the same fundamental functionality. Both Graylog and Kibana have their own pros and cons. It totally depends on the organization, which one to choose according to requirements after doing a detailed analysis.