This tutorial will elaborate on the difference between Kibana and Elasticsearch through the following outline:
What is Elasticsearch?
Elasticsearch is a well-liked open-source distributed analytical search engine and database that are usually utilized to store unstructured and semi-structured data. It stores that in documents in JSON format and uses REST APIs to play with Elasticsearch index, document, and data. It does not have its own UI but can integrate with the user’s UI and make the search experience more optimized.
Key Features of Elasticsearch
The following are the key features of Elasticsearch:
- It is considered as the heart of Elastic stack and is tightly integrated with ELK tools.
- Elasticsearch is a server as a search engine and database to access and retrieve data.
- It provides us with full-text search, analytical capabilities, and document indexing.
- It also uses Query DSL to handle and support complex queries.
- It works with Rest APIs through which users can interact with Elasticsearch and stored data.
- It stores and retrieves data from documents in JSON format.
Note: In order to use and install Elasticsearch on Windows, “Install Elasticsearch With .Zip File on Windows”.
What is Kibana?
Kibana is another important tool of the Elasticsearch community that is utilized to analyze and visualize Elasticsearch data in representative form. Kibana is basically serving Elasticsearch to manage data from a web-based GUI (Graphical User interface). It is tightly integrated with Elasticsearch and analyzes data using different tools such as pie charts, line graphs, heap maps, and histograms. You can say that Kibana is a GUI version of Elasticsearch. It is also utilized to manage and monitor Elasticsearch data.
Key Features of Kibana
Here are some key features of Kibana:
- It is a visualization tool that offers data visualization through different components such as Kibana Lens, Geospatial analysis, Data Tables, Canvas, Charts, and so on.
- It provides a friendly user interface for building and executing queries such as a visual query builder component.
- Users can execute Elasticsearch complex queries in an easy way using the Kibana console.
- Kibana is tightly integrated with Elasticsearch and fully utilized to serve Elasticsearch and also offers visualization and monitoring tools to analyze and manage data.
Note: To install and set up the Kibana tool for Elasticsearch, go through our provided guide “How to Setup Kibana For Elasticsearch”
Difference Between Elasticsearch and Kibana?
| Elasticsearch | Kibana |
| It is an analytical search engine and database that is used to store and analyze data | It is a visualization tool that is used to manage and analyze data stored by Elasticsearch. |
| It does not have its personal UI but can be integrated with the user’s UI | It is a web-based GUI that is specifically used for Elasticsearch and you can say that it is serving Elasticsearch. |
| All ELK tools are tightly coupled with Elasticsearch | Kibana is tightened and integrated with Elasticsearch. |
| It usually stores and extracts data from documents in JSON format | It can retrieve, and analyze data in visual form using Pie charts, histograms, Kibana lens, and so on. |
| Elasticsearch major focuses on storing, searching, analyzing, and indexing large volumes of raw or bulky data. | Kibana is best in data visualization, exploration, and analyzing data in representative form. |
That is all about Elasticsearch and Kibana.
Conclusion
Elasticsearch and Kibana are both major components of ELK or Elastic stack. The key difference between these two tools is Elasticsearch is majorly responsible for storing, analyzing, searching, and indexing large data. In contrast, Kibana is a visualization tool that provides ease to Elasticsearch users by offering data visualization and analysis through different tools such as Data tables, Kibana lens, histograms, and so on. In short, Kibana is serving Elasticsearch and providing it with a GUI interface. This post has demonstrated the difference between Elasticsearch and Kibana.
