If you are in IT operations, you must have heard about Kibana and Splunk: two much-talked-about tools. But, do you know which one would be the right pick for you? This article takes you through a brief comparison between Kibana vs Splunk so you can make a better decision. Let’s have a read ahead.
An open-source exploration and visualisation tool, Kibana is used for time-series analysis, log analysis and application monitoring. Along with this, it also offers inbuilt features, such as statistical graphs (in the form of line graphs, pie charts, histograms, and more. Kibana is a part of the ELK stack; thus, it even offers built-in integration with the Elasticsearch search engine.
Talking about Splunk, on the other hand, it is a visualisation software that is used to evaluate machine-generated data and logs, web applications, security, and application monitoring. This tool represents data in the inbuilt dashboard with the help of graphs and more.
While both the tools have outstanding features, choosing one between the two would be a close call. So, in this post, you’ll find an in-depth comparison between Kibana vs Splunk that will help you make a better choice.
Kibana vs Splunk - Table Of Contents
Kibana is a data visualisation, source-available dashboard software that is offered by Elasticsearch. This tool offers visualisation capabilities along with content indexed on the Elasticsearch cluster. You can create maps, pie charts, scatter plots, line plots, and bars to represent large volumes of data.
Moreover, Kibana also offers a presentation tool, known as Canvas. With this tool, you can create slide decks that extract live data directly from Elasticsearch. Also, the combination of Kibana, Logstash, and Elasticsearch, known as the Elastic Stack, can be used as a service or product.
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Splunk is one of the famous American softwares that help with searching, monitoring as well as analysing machine-generated data. To accomplish this task, Splunk uses a web-style interface. With this software, you can easily capture, index, and correlate real-time data in a completely searchable repository.
From there, the software effortlessly generates visualisations, dashboards, alerts, reports, and graphs. Splunk makes use of machine data to identify data patterns, offer metrics, diagnose issues and provide intelligence for operations.
When it comes to choosing the best tool between Kibana vs Splunk, here are some additional factors that should be considered:
The Splunk pricing is based on daily consumption of data that starts at a minimum of $5400/GB as a perpetual licence and $200/GB manually.
On the other hand, Kibana is a free tool. However, if you want to use it as a hosted service, you will have to pay approximately $45 per month.
In Kibana, a query is based on the “Lucene query syntax”. However, it is still being made available for customers under the query bar. Updates, such as simplified syntax and scripted field support were introduced in Kibana 7.0. Choosing this legacy query language, users do have the option to use JSON-based Elasticsearch query.
As far as executing a query in Splunk is concerned, the Snap Pack is used there. A Splunk query is generally used in Splunk software to run certain operations. To extract information from data and define log files through machines, this query language is used in Splunk.
In Kibana, visualisation is presented through the methods of tables and charts. In this tool, a query is automatically applied to the dashboard’s elements. User management offered in Kibana is distinct with the assistance of hosted ELK solutions.
In Splunk, the user interface lets you edit or add new components to the dashboard. Several users can create a customised dashboard. In Splunk, the control for several users can be configured differently.
In Kibana, if non-configured fields have to be searched, the properties for it will be pre-defined for aggregation over the properties of the log.
In Splunk, if you have to search non-configured fields, it lets you do so by converting the format according to the same.
In Splunk, you will not find any varieties at present.
In Kibana, as of now, there are three primary varieties that are linked with the tool, such as
The open-source ELK stack platform that is maintained by Elastic.
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To understand the difference between Kibana and Splunk in a better way, here is the table you can refer to
|It is a part of the ELK stack.||It is a proprietary standalone service/software.|
|It uses Apache Lucene’s syntax for queries.||It uses a custom-written Search Processing Language (SPL).|
|There are a lot of things that require improvement to offer more efficiency.||It is powerful as far as data analysation and processing are concerned.|
|It comes with a variety of detailed documentation and has several open-source platforms for discussion and sharing information.||It has huge documentation and customer support to resolve issues.|
|It is completely open-source and free. The setup is easy and there are several tutorials available.||It is licensed and charged. The software could be quite expensive for some people.|
|It majorly concentrates on monitoring tools.||It majorly concentrates on log analysis.|
|It is quite new and growing quickly. The tool is relevant to the needs of the present era and provides several advanced features.||It is an old product and has an established community.|
|Kibana is interactive and its UI is user-friendly.||Splunk offers a dashboard for the purpose of analysis visualisation but it is not much interactive in comparison to Kibana.|
|Kibana does not support debugging.||Splunk offers to debug and troubleshooting support.|
|Kibana does not support every type of data format but it allows third-party integration to send data in the preferable format.||Splunk supports every data format, such as JSON, log files, .csv, etc. Also, it is flexible with third-party integrations as well.|
|StackOverflow, Netflix, and LinkedIn are some organisations using Kibana.||Adobe, Cisco, and Bosch are some organisations using Splunk.|
To understand the key difference between Kibana and Splunk, here are some points:
At a glance, you will find out that both Kibana and Splunk come with their own pros and cons. Choosing a tool is absolutely based on the system and the requirements. If you want a tool for applications that need consistent backend support and robust, fast analysis, you can go with Splunk. However, if you think you will not be able to afford Splunk but still require real-time monitoring, you can go with Kibana.
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