Data Visualization Tools: Flot vs. Highcharts vs. D3.js

by Alex KhizhniakAugust 27, 2013

Our new research paper compares three popular JavaScript libraries, evaluating how they manage massive data sets and enable real-time visualization.

Table of Contents

Preview a comparison table

Today, web applications deal with massive data sets that require highly performant systems for processing and analysis. However, information becomes even more valuable, if you can efficiently visualize it.

Our Lead Front-End Engineer Igor Zalutski has prepared a comparison of three wide-spread, yet different, JavaScript libraries to see how they cope with big data and real-time visualization. The tools were selected based on popularity, performance, implementation approach, and relevance:

Flot, an open-source jQuery plug-in designed for drawing diagrams in Canvas
Highcharts, one of the most popular proprietary libraries
D3.js, a large open-source framework for data visualization

Below is a brief comparative table that will give you a general idea of what big data and real-time visualization capabilities you can expect from these tools.

An evaluation of Flot, Highcharts, and D3.js

For those interested in the topic, a comparison table on Wikipedia may also be useful—however, it only focuses on feature availability.

To get a more detailed analysis of Flot, Highcharts, and D3.js with 16 sample diagrams, a vendor-independent overview, as well as information on required code size, platform support, etc., download the full research paper.

Alex Khizhniak is Director of Technical Content Strategy at Altoros and a cofounder of a local Java User Group. Managing distributed teams since 2004, he has gained experience as a journalist, an editor-in-chief, a technical writer, a technology evangelist, a project manager, and a product owner. Alex is obsessed with AI/ML, data science, data integration, ETL/DWH, data quality, databases (SQL/NoSQL), big data, IoT, and BI. The articles and industry reports he created or helped to publish reached out to 3,000,000+ tech-savvy readers. Some of the pieces were covered on TechRepublic, ebizQ, NetworkWorld, CIO.com, etc. Find him on Twitter at @alxkh.