10 Free & Open Source Data Visualization Tools

Nilam Oswal

Nilam Oswal

Senior editor

Parul Saxena

Chief editor

Last updated: February 10, 2021

You cannot name a successful and professional field that does not require data visualization. The concept has a significant role in anyone’s career. Research and businesses specifically have great use of visualization tools. These kinds of tools help to create a clear representation of data that paints a good picture of the improvements or opposing factors, as well as it gives a good overview of research information.

What is Data Visualization? 

When a set of data or information is represented visually by utilizing colors, graphs, and charts, it is called data visualization. It is not just a data management process, but it has unique ways of showing the data so that one person or a company can quickly grasp it. ‘Open source’ software is customizable, and the source code is open for developers. If you want a different type of software with specific features for research, business, or personal use, you can code yourself or hire a coder to makes changes to an open-source tool to make it suitable for you.

Fortunately, there are free data visualization tools that don’t require any cost to be utilized. Such open-source data visualization tools come with different features and themes. Few of them are on the top when it comes to user experience. Here are the top 10 free open visualization tools that can help one’s individual career, offices, or businesses.

Best Free & Open Source Data Visualization Tools

1. Gephi – Great tool for scientists and data analysts

gephi

Gephi is a leading software in the field of data visualization and mostly used for professional service. It creates a 3D visualization of big data and finds the patterns within them. It has been a massive name since its release in 2010. 

 

Pros

  • Simple to use
  • Easy to convert data into CSV format 
  • Visualization is easy to go through and customize 

Cons

  • Exporting into an image or HTML document is not available.
  • Hard to customize the text for making it easily readable. 

2. RAWGraphs – Special tool for designers and vis geeks

rawgraphs

RAWGraphs makes complex data easy to understand with an eye-catching format. It can be described as a mixture of Microsoft Excel and Adobe Illustrator. The first version of this outstanding free tool was released in 2013, and it has gained more than 500,000 sessions. 

 

Pros

  • Many visual options with eye-catching views.
  • Exporting option in SVG and PNG format. 
  • Easy to insert data. 

Cons

  • Needs developer support to customize it. 
  • Basic charts are not present. 

3. Plotly – Best for businesses

plotly

Data scientists who require data visualization but don’t have any programming knowledge can use Plotly. With Plotly, one can also create a web app.

 

 

Pros

  • Web-based feature. 
  • Preferred for small to enterprise-level business.
  • Easy to import and edit the data. 

Cons

  • No apps for Android and IOS platforms.
  • It can be relatively hard to use.

Looking for Data Visualization Tools? Check out SoftwareSuggest’s list of the best data visualization tools

4. Avizo – Industrial data visualization tool

avizo

Developed by Thermo Fisher Scientific, Avizo is relatively sophisticated software that was launched in 2007 and now has a very modern look. Interactive visualization is pretty unique for Avizo and mostly suited for professional usage. 

 

Pros

  • Usable for many scientific research fields. 
  • High-tech probing tools more options. 
  • Highly suitable for professional fields. 

Cons

  • Complicated to get a grasp. 
  • Prior knowledge about 3D graphs is required. 

5. D3.js – Best option for news sites and database

d3

The JavaScript library, D3.js, is well-known in the areas of online sites. The triple ‘D’ stands for Data-Driven Documents. It uses SVG, HTML5, and CSS to create user-friendly visualization. Founded in 2011, this software has been widely used in specific areas. 

 

Pros

  • Very simple to use. 
  • Lightweight library. 
  • Customization and navigation on data are pretty easy.

Cons

  • Not supported in old browsers. 
  • A creative visual design graph is hard to make. 

6. Datawrapper – For journalists, developers and designers

datawrapper 

Developed by Datawrapper GmbH, Datawrapper specializes itself for being fast-paced and for office usage. It provides customizable visualized data with a lot of different options for different offices and preferences.

 

Pros

  • It does not require one to have coding experience.
  • It can be customized for being open source.
  • Variety of options for different types of visualization. 

Cons

  • The data is stored in the software’s server. 
  • Font and color customization is a tough process. 

7. Chartist.js – Simple format for primary usage

chartistjs

If you need a more simplified version of standard visualization tools, Chartist.js is a perfect choice. It is an online tool that is used by many well-known brands for good-quality analytics. 

 

Pros

  • It provides fast results. 
  • The charts are fully responsive. 
  • Easy control features. 

Cons

  • Needs a minimum Android version of 4.4.
  • Not supported in Safari 7.

8. ColorBrewer2 – Made for maps and navigation

colorbrewer

Navigation data is very complicated to place and use. For this, there is an open-source tool with a fancy name. ColorBrewer2 uses different bold colors that make it easier to differentiate information from each other. 

 

 

Pros

  • Easy to use and import the information. 
  • Information is very clear to see.
  • Free and open source for customization. 

Cons

  • Not much responsive 
  • No data chart. 

9. Cytoscape – Perfect for bioinformatics

cytoscape

Cytoscape is a professional data visualization tool for showing molecular data, and it is greatly used in bioinformatics. It is written in Java and was released in 2002. Having the ability to visualize complex data and finding similarities, it is mostly suitable for professional usage. 

 

Pros

  • Wide range of formats.
  • The tool has familiarity with gene ontology formats. 
  • Has more advantages for biological data.

Cons

  • Not all plugin is supported on specific platforms.
  • User needs to have proper knowledge about it for best performance.

10. NodeBox – Good level visualization

nodebox

NodeBox is a fast and straightforward solution for visualized data with all mathematical information. It supports python programming code, and one can easily customize it since it is open source. It can be described as simple yet complex because it has a lot of formats. 

 

Pros

  • Easy to use. 
  • Simple to complex formats. 
  • Easy to navigate and import data. 

Cons

  • Not suitable for very complex issues. 
  • Texts are hard to customize.
Nilam Oswal
Nilam Oswal is a Content Marketing Head and Brand Strategiest at SoftwareSuggest. When she's not hard at work, she can be found wandering, reading, and just generally having a good time in life.

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