Compare Top 14 Data Visualization Tools of 2019

What are the best data visualization tools?

Well, that’s a tricky question, because there are so many different types of data visualization tools. These tools meet different requirements and demand corresponding skills for users.

In this article, I reviewed what I consider to be the 6 mainstream types and 14 top data visualization tools. The comparison covers the use of these tools, their respective advantages, suitable crowd, and price. Hope can help you find the best data visualization tool for you.

1.Code tools

The code tools are characterized by more freedom of data parameters, increased data processing capacity, and more diverse data play.
Javascript, Python, and R are popular data visualization programming language nowadays, and they all have rich visualization library.

D3.js

D3.js is an open-source JavaScript library that’s used to create data visualizations with HTML, SVG, and CSS. D3 allows you to handle the Document Object Model (DOM) based on your data.

D3 is the best chart gallery, which also can be applied with Python or R.
I would recommend you use Javascript or R other than Python considering the Python-nvd3 library last updated in 2016, which is outdated compared to others. D3.js is highly flexible while hard for newbies.

Suitable crowd：front-end developers who are good at Javascript, SVG or DOM
Cost: Free

Plotly

Plotly is an open-source, interactive, and browser-based python graphing library. It enables creating complex interactive charts that can be smoothly applied to dashboards or websites. It is built on top of the d3.js visualization libraries. Therefore, Plotly is an advanced chart gallery.

Its distinct advantage is creating multi-chart visualizations when comparing datasets. Besides, you can set up Plotly to work in online or offline mode or jupyter notebooks.

Suitable crowd：front-end developers who are good at Python
Cost: Free with commercial plans

gglot2

ggplot2 is a data visualization package for the statistical programming language R. The idea of ggplot2 is to separate the drawing from the data. It is to make the drawing according to layers, which is conducive to architectural thinking.

For professionals who need making plots involving mountains of data, ggplot2 is the best choice. It is easy and quick to build plots in layers to display complex stories. You can define various underlying components and simple functions to achieve complex charts.

Suitable crowd: professionals with R knowledge
Cost: quote-based

2. Visual Reporting or BI

If you are going to use professional data visualization while having no programming background, you should try the following data visualization tools with drag-and-drop elements. In addition to visualization, such tools generally focus on database connection, data analysis, and data processing.

Beginners do not need to master too many such tools. Excel, FineReport, and Tableau are the first choice. Excel is widely used; FineReport is easy to create complex reports and dashboards, Tableau is the best for data analysis via visualization.

Excel

As a part of Microsoft’s business office suite, you must be familiar with Excel. Excel offers some standard charts, from unit heat maps to scatter plots. Although it’s an entry-level tool, it’s a great way to get started if you want to explore data.

Suitable crowd: Anyone
Price: Free with commercial plans

FineReport

FineReport is a reporting software while being distinct at data visualization, primarily visualizing your data via reports or dashboards with impressive HTML5 charts including 3d and dynamic effects.

What impressed me most is that it saved me much time to develop reports. Before using FineReport, we made 10 excel tables for ten stores, which were very troublesome. But with FineReport, we just need to use the parameter query in one template, and then export data in batches.

The other features worth mentioning is data integration and data entry in terms of datasets for data visualization.

Suitable crowd: for report developers and BI engineers
Price: Free for personal use, Quota-based for companies

Tableau

Tableau is a data analytics and visualization tool. Almost every data analyst will mention Tableau. It has standard built-in analysis charts and some data analysis models.

Unparalleled capacities of visualizing information are on top the list of Tableau software benefits. Its graphs and color schemes are very amazing. The application’s data visualizing quality is superior to what Tableau software competitors offer.

The only limitations in terms of data visualization are that Tableau does not offer 3D charts and no custom visual imports.

Suitable crowd: for BI engineers and data analysts
Price: Free trial with commercial plans

3. Maps

Map visualization is used to display the geographically related data and present it in the form of maps. This kind of data expression is more precise and intuitive. Although the tools mentioned above covers part of map types, the map visualization tools provide more opulent choices, and most of them are lightweight.

Leaflet

Leaflet is an open-source Javascript library for interactive maps. Weighing just about 38 KB of JS. The distinct advantages are the interactive features such as keyboard navigation, multiple maps scaling methods. You can display your map both on desktop and mobile platforms. Besides, the well-documented APIs enable developers to customize map projections to meed needs.

Suitable crowd: for developers with javascript skills
Price: Free

Power Map

If you haven’t used Power Map before, I would say you missed a treasure. Power Map is an Excel Add-in developed based on Bing map, which is part of its BI suite and is used to map geographic data. Even non-technical users can plot geographic and temporal data on a 3-D globe or custom map without coding.

Suitable crowd: Excel users
Price: Free

4.Infographic Tool

Infographic is a type of data visualization to visualize your data more vividly. It helps you convey your information in a storytelling way that can engage your audience. The most popular are Canvas, Picktochart, and Visme. Here I will compare the last two tools.

Piktochart

Piktochart is a web-based application designed to make infographics that offer hundreds of infographic templates. The “download as blocks” feature is on the top of the “awesome” list. Besides, section manipulation functionality is excellent. You can conveniently copy sections, move them, or delete them. However, no robust media HTML5 export options may affect the user experience when you want to show your works offline.

Suitable crowd: Anyone
Price: Free with commercial plans

Visme

Same as Piktochart, Visme provides rich infographic templates and enables users to create maps. However, compared to the tactic infographics in Piktochart, the infographic in Visme can be animated and interactive. Another feature that user-friendly is the keyword search function for the related templates. The only con of Visme is it requires longer learning time than Piktochart.

Suitable crowd: Anyone
Price: Free with commercial plans

5.Net-work graphs

Network graphs help you simplify complexity and find relationships between data. The node-link structure makes data connection intuitive. You can apply network graphs to law enforcement, infrastructure management, anti-fraud, and cyber-security.

Keylines

Keylines is a lightweight JavaScript toolkit for network visualization using HTML5, compatible with all any browser, device, server, or database.

It provides eight automatic graph layouts for detangling links to reveal patterns and anomalies. And it puts more freedom into the user’s hands that allow users to filter network, combine node, analyze the social network.

Suitable crowd: JavaScript developers
Price: Free with commercial plans

Gephi

Gephi is an open-source software package that is professional in network analysis and visualization. It has an easy-to-use interface where you can get to the tools you need quickly without much training or learning.

You can import data in CSV format easily, and once the correct data is loaded and mapped together, Gephi generates a graph automatically. However, the export feature is not very user-friendly that you can not export your design to an image or HTML document.

Suitable crowd: Non-technical users
Price: Free

6. Large-Screen Visualization

Large screen visualization is in demand in situations such as in meetings or the exhibitions. Some companies also put TV dashboard in offices for employees to track KPIs.

Ali DataV

The large screen of ET City Brain is made with DataV. It is a drag-and-drop visualization tool of Alibaba Cloud, which is mainly used for big data visualization of business data combined with geographic information. You can often see them in places like exhibition centers and enterprise control centers.

You do not have to program, and you can generate a visual large screen or dashboard with a simple drag and drop operation.

Suitable crowd: IT developers
Price: Quote-based

FineReport

As mentioned before, FineReport is reporting tool, but its performance in displaying dashboard across any large screens is excellent.
It can integrate data from business systems such as OA/ERP/CRM, and play business data on large screens in real-time.

Compared to Ali DataV, FineReport is more suitable for enterprises because of its application structures. It is usually used in places like the exhibition center, monitoring center as well as in the office.

Suitable crowd: IT developers
Price: Quote-based

Original source: http://www.finereport.com/en/about-finereport/compare-6-types-and-14-data-visualization-tools.html