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Table of contents
1.
Introduction
2.
Understanding Elasticsearch
2.1.
Features of Elasticsearch
2.2.
Disadvantages of Elasticsearch
3.
Understanding Kibana
3.1.
Features of Kibana
3.2.
Disadvantages of Kibana
4.
Elasticsearch vs Kibana
5.
Frequently Asked Questions
5.1.
Can we use Elasticsearch without Kibana?
5.2.
What is Kibana used for?
5.3.
What is the difference between Elasticsearch vs Kibana?
5.4.
What are the uses of Kibana?
6.
Conclusion 
Last Updated: Mar 27, 2024

Elasticsearch vs Kibana

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Introduction

Elasticsearch is a powerful search engine and Kibana is a data presentation tool. They are together called the ELK (Elasticsearch, Logstash, and Kibana) stack, which is used for searching, analyzing, and visualizing data. 

Elasticsearch vs Kibana

In this article, we will be discussing the key features of Elasticsearch and Kibana, followed by the differences between Elasticsearch vs Kibana.

Understanding Elasticsearch

Elasticsearch is a popular search engine that helps users find and get information from big data sets easily. It does not follow the old table schema like the SQL databases. It uses the Lucene search engine to store data. Elasticsearch can manage and analyze large datasets, thus making it easier to search, filter and arrange the databases. 

Features of Elasticsearch

The key features of Elasticsearch are:

  • It helps users to quickly search for the required words or group of words in big datasets.
     
  • It provides real-time search results. Thus when the user updates any data, it can be searched right away, making it a good choice for real-time uses.
     
  • It comes with the full-text search feature. It can be used to search through the entire document.
     
  • It can handle big sets of data and grow as the data increases, making it a good choice for large projects.
     
  • It offers advanced search features like fuzzy matching, auto-completion, and many more.
     
  • It is free to use and has many developers supporting it.

Disadvantages of Elasticsearch

The disadvantages of Elasticsearch are:

  • It requires a complex setup and users with good technical skills, thus making it difficult to apply and maintain it.
     
  • It needs a lot of computer memory to work which can be a problem if the computer has less resources.
     
  • The distributed design of Elasticsearch can sometimes lead to data loss in cases of system failure.
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Understanding Kibana

Kibana is a data visualization and presentation tool. It is used to analyze and view the data that is stored in Elasticsearch. Kibana helps users to create engaging charts, graphs, panels, and dashboards to get useful information and monitor our data. 

Kibana is used in business decision making, monitoring the health and usage of applications, and data analysis to easily understand and present information from big and complex datasets.

Features of Kibana

The key features of Kibana are:

  • It connects the Elasticsearch data store of the user to access and work with their data. 
     
  • It comes with many features like charts, graphs, maps, and tables that can be used to monitor our data. 
     
  • In Kibana, we can select the data that is to be analyzed. Kibana can also be used to filter data based on time periods, categories, or other labels.
     
  • It also allows users to create dashboards by combining many panels. With dashboards, users can monitor a number of metrics at the same time.
     
  • It offers some new features like Geo Maps, Time Series, and Machine Learning capabilities.
     
  • It allows us to share our results with our team. To do this we can export and share visualizations and dashboards. We can also receive timely reports regularly.
     

Next, let us discuss the differences between Elasticsearch vs Kibana.

Disadvantages of Kibana

The disadvantages of Kibana are:

  • It requires some understanding of Elasticsearch. Hence it can be difficult for beginners. It is also a complex task to set up Kibana in the system.
     
  • It asks for a lot of computer resources when working with big datasets, which also requires a better hardware system.
     
  • It requires the internet to work. This can become an issue in places where there is no internet connection. 

Elasticsearch vs Kibana

The difference between Elasticsearch vs Kibana are as follows:

Factor Elasticsearch Kibana
Purpose Elasticsearch acts like a powerful search engine and data store. Kibana is a data visualization tool.
Querying and Aggregation Elasticsearch can perform advanced searches, handle complex queries, and summarize data with grouping. Kibana offers a user-friendly interface that allows users to create charts, graphs, etc. This in turn helps in monitoring the data easily.
User Interface It offers a way for developers to interact with its capabilities using a RESTful API. Kibana provides a user-friendly interface to view and understand data easily.
Data Visualization Elasticsearch is very useful for fetching and indexing data. It returns results in JSON format. It changes unstructured data into visually appealing charts, graphs, and maps.
Integration with Elastic stack Elasticsearch is the key component for storing and indexing data. Kibana works along with Elasticsearch to view and analyze the data stored in Elasticsearch.

Also check, Difference Between Data Analyst and Business Analyst

Frequently Asked Questions

Can we use Elasticsearch without Kibana?

Kibana can work with elasticsearch and depends on it for storing data and fetching any information. Hence Kibana cannot work without Elasticsearch. While Elasticsearch can be used independently as a search engine to analyze and store data.

What is Kibana used for?

Kibana is a data visualization tool that is used by researchers to see and understand their data better. It lets users change the data stored in Elasticsearch into charts and dashboards which are easy to understand. This helps in making informed decisions based on the results found.

What is the difference between Elasticsearch vs Kibana?

Elasticsearch is a powerful search engine that is also used for storing data. Kibana, on the other hand, is a data visualization tool. They work together in the Elastic Stack, where Elasticsearch manages data storage and search, and Kibana analyzes and visualizes data. 

What are the uses of Kibana?

Kibana allows users to see and share important information in a clear and visual way. It is used in many areas like business decision-making, monitoring the health and usage of applications, and data analysis to easily understand and present information from complex datasets.

Conclusion 

Elasticsearch is a search tool that allows data storage, retrieval and real-time querying of big data whereas Kibana is used as a visualization tool to create dashboards based on the data stored in Elastisearch.

We hope this blog has helped you understand the difference between Elasticsearch vs Kibana.

Keep learning! We suggest you read some of our other articles related to Data analysis: 

  1. ELK stack
  2. Elasticsearch interview questions
  3. Amazon Elasticsearch Service
     

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