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Top 10 JavaScript Libraries for Data Visualization [2024]

JavaScript data visualization libraries help developers create interactive charts, graphs, and other visual components that bring data to life. Basically, JavaScript data visualization libraries have become the go-to tools for developers. These libraries don’t just create charts and graphs ; they help tell stories through data, making it easier for people to understand and act on complex information. Whether you’re building a business dashboard, a website, or a scientific application, being able to visualize data effectively can make all the difference. This helps users to grasp complex information quickly and intuitively. Today's data-driven landscape makes it crucial to be able to turn complex information into simple , entertaining stories.

We have curated the top 10 javascript libraries for data visualization in the table below.

Table of Content

What is Data Visualization?

Top 10 javascript libraries for data visualization, 1. d3.js (data-driven documents), 2. chart.js, 3. plotly.js, 4. highcharts, 5. google charts, 6. fusioncharts, 9. amcharts, 10. apexcharts.

Choosing the right JavaScript library for your data visualization needs is crucial. With so many options out there, it’s easy to feel overwhelmed. Do you need something that’s highly customizable? Or maybe you’re looking for a tool that’s simple to use but still powerful enough to handle large datasets? This article explores the top 10 JavaScript libraries for data visualization in 2024, breaking down their features, strengths, and weaknesses to help you find the perfect fit for your project.

This article explores the top 10 JavaScript libraries for data visualization , highlighting their advantages, limitation, and features. You should consider using these JavaScript libraries for data visualization when selecting a solution for your next project.

Data Visualization involves representing information visually such as maps, charts, or graphs. It makes complicated data structures easier to understand; analyze; and communicate. Good data visualization improves user experience; encourages analysis of data sets; and produces memorable narratives.

Factors to Consider When Choosing a JavaScript Data Visualization Library

Before diving into the libraries, it's essential to consider these key factors:

• Chart Type Support: Does the library offer the specific chart types you need (bar, line, pie, etc.)?
• Learning Curve: How hard is it to learn and integrate this library into your project?
• Customization: Can you tailor the look of the visualizations as much as possible?
• Interactivity: Are there any interactive features like tooltips, zooming in or out, panning, etc.?
• Performance: Can the library handle large datasets efficiently without sacrificing performance?
• Community & Support: Does the library have a large and active community for help and resources?

Here are the Top 10 JavaScript libraries for Data Visualization with their features known for converting raw data into engaging visuals, each tool has it's own distinctive features and capabilities.

Let us see each one of the javascript data visualization libraries in detail them in detail with their advantages and limitations.

D3.js is an effective JavaScript toolkit used to produce an interactive representation of dynamic data. This tool's ability to let software developers correlate data with DOM elements makes it stand out from the competition and enables greater customization of the visualization creation process than similar tools. D3.js offers an adaptable toolkit for producing beautiful data visualizations , from simple charts to complex geographic maps.

• Unmatched flexibility and control over visualization design.
• Extensive support for complex data structures and interactions.
• Wide range of visualization possibilities, including maps and network diagrams.
• Active community and wealth of online resources for learning and support.

Limitations

• The steep learning curve, especially for beginners.
• Requires a solid understanding of web technologies such as HTML , SVG , and CSS .
• Development time may be longer due to its low-level approach.

For simplicity and versatility, Chart.js is the best option when it comes to easily creating visually beautiful charts without having to do much setup. The API being intuitive, with support for numerous chart types such as line, bar, pie, radar , etc., Chart.js enables developers to convert data into colorful representations that can be used for various purposes.

• Easy-to-use API , suitable for developers of all skill levels.
• A lightweight footprint and fast rendering ensure optimal performance.
• Responsive design adapts seamlessly to different screen sizes and devices.
• Extensive documentation and active community for guidance and support.
• Limited customization compared to more advanced libraries like D3.js .
• Advanced features may be lacking for complex visualization requirements.
• Performance may degrade with very large datasets or intricate animations.

Data scientists and analysts will find Plotly.js as an essential addition to their toolkit for bringing their insight to light using different types of charts with rich features. Users can seamlessly integrate it with Python and R making it smooth for one to explore and communicate information about data. For continuously updating visualizations filled with news flashes or reports on progress accompanied by detailed metrics that are changing over time among others; this is the best way to go because you get real-time communication.

• Seamless integration with Python and R for streamlined data analysis.
• Extensive collection of chart types, including scatter plots, line charts, and 3D visualizations.
• Interactive features such as zooming, panning, and tooltips enhance user engagement.
• Strong community support and documentation for easy adoption and troubleshooting.
• Complexity may pose a challenge for novice developers.
• Performance may suffer with large datasets or complex visualizations.
• Certain advanced features may require additional configuration or customization.

Highcharts has a rich set of tools and a strong range of charting features that are widely used by developers who want to have professional visualization. It comes with support for various kinds of charts and exports to facilitate the development of artistic appearances.

• Broad customization possibilities and extensive reference materials.
• Charts can be exported to various formats like PNG, JPEG, and PDF .
• Integration with popular frameworks and platforms is seamless.
• These pages are designed to look great on all devices and screen sizes.
• Licensing restrictions may apply for commercial use and certain features.
• Limited support for extremely large datasets or complex visualizations.
• Performance may degrade with intensive animations or interactions.

Google Charts rely on Google’s infrastructure for its smooth inclusion in other Google products resulting in a flexible and user-friendly approach to data visualization. The presence of different types of charts, and intuitive API makes Google Charts a good choice for anyone who wants to build interactive visualizations easily.

• Easy integration with Google Sheets and other Google products.
• Intuitive API and extensive documentation for easy adoption.
• A wide range of chart types and customization options are available.
• Cross-browser compatibility and responsive design ensure optimal performance.
• Customization options may be limited compared to other libraries.
• Reliance on Google's infrastructure may raise privacy or dependency concerns.

FusionCharts is known for being highly sophisticated as well as flexible in offering a wide range of graphing instruments that build up visually impressive presentations. By offering numerous chart types and advanced features, this service provides sophisticated approaches for transforming raw data into fascinating stories about businesses.

• Extensive collection of chart types and advanced features.
• Seamless integration with popular frameworks like Angular and React .
• Support for annotations, export to CSV/PDF, and multi-language support.
• Responsive design and excellent documentation facilitate ease of use.
• Licensing fees may apply for commercial use and certain features.
• Steeper learning curve compared to simpler charting libraries.
• Performance may be impacted by very large datasets or complex visualizations.

The C3.js library simplifies the creation of reusable and interactive charts by utilizing the power of d3.js , an effective javascript library. C3.js is a higher-level API that uses D3.js , making reusability and interactivity easier to implement in charts. Furthermore, It supports out-of-the-box interactivity. This reduces development time yet still allows room for customization which makes it a popular choice among developers who seek simplicity without rigidity.

• Simplified API and intuitive syntax for quick development.
• Easy integration with existing projects and frameworks.
• Customizable and reusable charts with minimal effort.
• Good performance for most use cases.
• Limited customization compared to D3.js.
• Advanced features may be lacking for highly complex visualizations.
• Performance may degrade with very large datasets or real-time updates.

Among the most popular features of ECharts developed by Baidu is its excellent rendering efficiency and support for real-time data updates. They are also built with strong visualization capabilities that can handle big data effectively. With a wide range of chart types and seamless integration inside famous frameworks, ECharts provides software developers with best-in-class tools to build dynamic & responsive visualizations.

• High-performance rendering and smooth animations.
• Responsive design and excellent support for real-time data updates.
• Extensive customization options and rich documentation.
• Seamless integration with popular frameworks and platforms.
• Complexity may pose challenges for novice developers.
• Limited support for certain chart types or advanced features.
• Performance may degrade with very large datasets or intensive animations.

A rich JavaScript library offering full-fledged JavaScript Graphs / Maps / Stock Charts libraries is amCharts . Moreover, charts different types of charts along with their advanced functionalities enable the users to create visually appealing data visuals while giving information based on the required circumstances.

• Extensive customization options and advanced features.
• Excellent documentation and support.
• Responsive design and good performance for most use cases.
• Complexity may pose challenges for beginners.
• Performance issues may arise with very large datasets or complex visualizations.

ApexCharts’s modern JavaScript charting library possesses a simple but powerful API for creating charts and graphs that are interactive . ApexCharts makes it easier than ever before to develop stunning, responsive visualizations with its lightweight footprint and seamless integration into widely used frameworks like React and Vue.js.

• Lightweight footprint and fast rendering.
• Seamless integration with popular frameworks like React and Vue.js .
• Extensive customization options and responsive design.
• Limited support for very large datasets or complex visualizations.
• Advanced features may be lacking compared to other libraries.
• Limited documentation and community support compared to more established libraries.

Must Read Top 10 Libraries for Data Visualization in 2024 Interactive Data Visualizations in JavaScript What is Data Visualization and Why is It Important?

Each JavaScript data visualization library has its own advantages and disadvantages. In order to make a correct decision about the right tool for their particular project needs, developers should consider there advantages, limitations and use cases meticulously. Whether it is making use of D3.js’ flexibility Chart .js’ simplicity or Fusion Charts ' sophistication, there are many options open for developers who wish to come up with stunning but informative visualizations that can be used to yield invaluable insights.

Top 10 JavaScript Libraries for Data Visualization [2024] - FAQs

Which is the most popular javascript visualization library.

D3. js is one of the most popular data visualization libraries used to manipulate documents based on data. It uses web tools like SVG, HTML, and CSS to create graphs, maps, and pie charts.

What is the easiest JavaScript chart library?

Highcharts is the best for easy chart creation as it has a well written documentation library that can help you get started easily.

What is the most popular charting library js?

Chart. js. is the most popular charting library according to GitHub stars and npm downloads.

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What kind of charts do I want to build? Pie charts, maps, lines, bars?

How large is the dataset, is the app used for web, mobile, or both, what’s the browser support for a given library, which javascript framework do you use, what kind of customization of the look and feel do you need.

• Flexmonster
• Webdatarocks
• Google Charts

Commercial JS Charting Libraries

To what extent does your app rely on data? It probably does in some way. Even if the app is not exactly business-oriented, you’d probably need data for the admin panel, the dashboard, performance tracking, and similar analytics features that users love so much.

Best JavaScript DataGraph Visualization Libraries 2024 :

• D3.js 

Visualizing data inside those apps and presenting them to end-users is a great responsibility. Companies build strategies around the charts, numbers, and tables they’re presented with, and often use them to choose whether to pursue business opportunities. Therefore, choosing the right tools can in some cases be the difference between making it and breaking it.

For a JS developer, the ability to visualize data is just as valuable as making interactive Web pages. Especially since the two often go in pairs. As JavaScript continues to gain popularity in the data visualization realm, the market is flushed with even new libraries with which to create beautiful charts for the Web.

How to Choose the Right JavaScript Data Visualization Library

For our internal purposes, we needed to better understand when to use them and why. We picked nineteen Javascript graph visualization libraries that are currently the most popular or interesting for building digital products and started a little study to see which one would work best for our projects.

To understand which data visualization library would work best for your projects, there are a number of factors to consider:

Some libraries support only a handful of types. Make sure you know which ones you need first.

Libraries based on SVG are usually better for smaller to medium datasets, as each element is a unique node and exists in the DOM tree. This also means that they offer a lot more flexibility by allowing direct access. Although you could make them work with large data sets with the help of some data aggregation algorithms, smart memory management, and other fancy tricks, going with Canvas-based tools for large datasets is the more reliable option here. Canvas is really fast.

Some libraries are better at responsiveness, while a few others have their own React Native versions like Victory.

Check your browser market share to figure this out.

Make sure your data viz library will go well with it. Using React? Going with a React-specific library might be a better option than using wrappers.

If you need some advanced animations, for example, you should take that into consideration, too. 

Note that in some cases, you may not need a JavaScript data visualization library at all. Sometimes it’s a better idea to write one from scratch using vanilla JavaScript. While the initial overhead is significant (especially when it’s your first time), for projects with custom, tailored charts such a move might pay off in the future

Sometimes it’s better to keep your sanity and spend more resources on the developing part rather than trying to bend libraries to fit your particular needs. Although it may sound scary at first, with an SVG-oriented mindset and few hours to experiment—who knows, it might actually be fun!

To see a real-life example of a Data Visualization app we built, check out Packet Analyzer .

If you are familiar with modern frontend frameworks, then Vue.js is especially great in this area and its reactiveness makes working with SVGs a breeze. Notice I’m talking strictly about SVG-based charting as it’s much easier to implement.

HTML5 Canvas is simply a drawing surface for a bitmap and it’s not aware of the objects drawn inside—they’re pixels, not actual DOM elements like they are in the case of SVG. If you want to make it interactive, you will need to handle all the logic yourself.

While Canvas-based approaches offer a performance edge with large datasets (1000+ elements) and careful manipulation, I wouldn’t recommend writing one from scratch—unless it’s a core feature of the product.

So when is it a good idea to use a library?

Either when you have an odd chart in the project, one that needs to be basic but good-looking, with all the bells and whistles (tooltips, legend, X/Y axis, etc.) or when the application demands standardized, responsive, and elaborate charts, especially when there’s more than one type.

In the end, we use libraries to keep ourselves from reinventing the wheel over and over again, and most of them have been around long enough to have factored in most use/edge cases. Oh, and they come with animations built-in, too.

It’s impossible to try all of them out in real-life scenarios, but below you’ll find a list I’ve compiled based on my own and others’ observations. Keep in mind that before you dive into one library, it’s always a good idea to see how it will integrate into your project. In the end, the choice is yours—so here’s a list!

If you’re not a large enterprise, open-source libraries offer more than enough options to choose from. If you have successfully answered the questions I mentioned above, you will probably find your perfect match fairly easily.

1. D3.js 

GitHub Stars: 100,000

D3 is one of the most popular JS libraries not just for data visualization, but also animations, data analysis, geo, and data utilities. It uses HTML, SVG, and CSS. It has a gigantic API and some say it’s not a data visualization library at all.

Everything you can probably think of can be done with this library, but it comes with its downsides. It has a steep learning curve and the documentation is outdated and confusing to navigate.

Much of the API exposes direct access to the DOM, which might clash a little with how modern frontend frameworks like React or Vue work. There are ways to work around that, though.

One involves so-called declarative data-driven documents (d4 in short), which suggests letting the framework manipulate the DOM and using D3 strictly for the data API. You can find more info and examples here .

Works with: anything

D3 GitHub D3 gallery

Want to know more about D3 possibilities? See how we visualized data of more than 4,4 million users of complex finance management platform with D3. Check out Cashdeck.

2. Recharts

GitHub Stars: 17,700

A data viz library was created for React users. Recharts uses D3 under the hood and exposes declarative components. It’s pretty light and renders SVG elements to create beautiful, interactive charts. It’s easy to use and the documentation is a blast.

Charts are customizable and the library itself provides some nice examples. It delivers great performance for static charts and includes built-in general chart tools like legend tooltips and labels. It can be laggy when dealing with multiple animated charts on the same page and large datasets, but it will work for most use cases.

What’s a bit troubling is the high number of unsolved issues on GitHub. These issues may not be critical, but creators don’t seem to drop by to answer them too often. So if you get stuck, be prepared to dig deep into the library.

Works with: React

Recharts GitHub Recharts examples

GitHub Stars: 9,300

A set of modular charting components designed specifically for React and React Native.

Victory does a good job providing fundamentals to create a chart.

Things like axes customization, labels, passing in different data sets for a single graph are all pretty straightforward, and tweaking styles and behavior is easy and intuitive.

It’s really effective and lets you build some nice-looking charts with minimal code. Definitely worth checking out for cross-platform apps.

Works with: React, React Native

Victory GitHub Victory gallery

4. React-vis

GitHub Stars: 8,100

It’s a simple Javascript graph visualization library created by Uber, which allows you to create all the usual types of charts: bar charts, tree maps, line, area, and more. Its API is quite simple and offers a lot of flexibility. It’s light and the animations are simple but fluid. It also allows you to write custom charts based on existing elements.

Its minimalist styling, however, may not fit everyone’s tastes (but I personally like it!). Although there aren’t too many on react-vis out there, the documentation is straightforward and easy to read.

React-vis examples

5. V Charts

GitHub Stars: 6,500

It's a good all-around tool for creating common charts with simple data configuration. It is based on Vue2.x and echarts. 

Works with: Vue.js 

Read more about the best Vue data visualization libraries here .

Also, check our latest Vue Migration Cheat Sheet:

6. Chartkick 

GitHub Stars: 5,800

Chartkick is a great tool not only for Vue . It enables you to generate charts that are functional and aesthetic. 

Works with: Vue.js, Python, JavaScript, React, Elixir, Ruby 

7. Flexmonster

It's a pivot table component for React Native. Great for visualizing business data. 

8. Webdatarocks 

A JavaScript pivot table component well compatible with React and other frameworks. It's great for data reporting with its aggregating, sorting, and filtering features. It's free to use in your Web browser. 

9. ApexCharts

GitHub Stars: 11,100

A rather neat library for SVG charts comes with a Vue.js and React wrapper. Its charts look great on different devices, and the library allows for customization and comes with comprehensive documentation. It can be laggy with larger datasets, so make sure it’s exactly what you’re looking for.

According to Juned Chhipa, the creator of ApexCharts, the library was created for easier zooming, panning, scrolling of data, placing informative annotations on charts, and more.

The library itself is new and there’s still a lot of room to grow, but if responsiveness and interactivity are especially important for you, it’s a nice-looking library worth giving a shot to!

Works with: React, Vue.js, plain JavaScript

ApexCharts GitHub ApexCharts examples

10. Chart.js

GitHub Stars: 56,100

A very popular open-source library with more than 55k stars on GitHub. It’s lightweight and lets you build a responsive chart using HTML5 Canvas elements. You can easily mix and match line and bar charts to combine different datasets, which is quite an awesome feature.

Chart.js offers you six different chart types by default, it supports responsiveness and is beginner-friendly. It’s also my go-to library for very large datasets. Definitely, one of the most interesting open-source libraries to check out.

Works with: React, Vue.js

Chart.js on GitHub Chart.js examples

11. Echarts

GitHub Stars: 49,600

This library created by Baidu is super useful for JavaScript data visualizations intended for the Web. It’s well-documented in English and works great with big datasets. It also supports both SVG and Canvas rendering.

Echarts on GitHub Echarts examples

GitHub Stars: 9,700

Nivo is a beautiful framework built on top of D3 and React, offering fourteen different types of components to present your data with. It was released in 2017, featured as "product of the day" on ProductHunt on August 20, 2017.

Nivo offers a lot of customization options and three rendering options : Canvas, SVG, and even API-based HTML. The documentation is exceptional and the demos are configurable and fun. It’s a high-level library and quite simple but offers less potential for custom visualizations.

Nivo GitHub Nivo website

13. Google Charts

An extremely popular Web service for charts that I simply couldn’t leave off the list. For many out there it’s the go-to JS library, as it provides multiple pre-built charts types, such as bar, line, area, calendar, geo charts, and many more.

For me, however, the library feels like overkill in most cases and, frankly, I wouldn’t recommend using it.

It’s free, but not open-source (pretty much like every Google product). It’s not responsive by default, but you can make it resize charts with some code.

There are different customization options, depending on the chart type, but it’s not exactly beginner-friendly. And you have to load it directly from a Google URL instead of an NPM package.

Works with anything

Google Charts website Google Charts gallery

Some libraries offer free versions for personal use, but you need to pay to use them in commercial applications. All of the libraries listed below are commonly used by big corporations. Why? Because all of them are truly comprehensive, customizable, and offer great customer support. If you’re an enterprise, you should check them out.

14. amCharts

One of the hottest charting libraries out there. Its beautiful design really sets it apart from the competition. amCharts lists Apple, Amazon, NASA, and many other prominent names as their clients, which is pretty impressive, to be honest.

amCharts is a commercial tool and their pricing starts at $180 per single website license. In return for a fixed fee, you get all types of charts you’d need, including geographical maps and great customer support, with response times averaging less than 3 hours. It sounds like a good solution for large companies.

Works with: Angular, React, Vue.js, plain JS apps, TypeScript

amCharts GitHub amCharts website

15. CanvasJS

Another commercial tool offering beautiful charts across different devices and browsers. It lacks some chart types, such as the network chart, sparkline, or gauge charts for example. Plus, its learning curve is quite steep.

On the other hand, it’s very fast, working smoothly even with as many as 100k+ data points, and provides four default themes that should be a good fit for most scenarios. Their client list is quite impressive, too: Apple, Bosch, Siemens, HP, Microsoft, and many more.

Works with: Angular, React, jQuery, plain JavaScript

CanvasJS website CanvasJS gallery

16. Highcharts

GitHub Stars: 10,400

A JS library released in 2009 JS, based on SVG with fallbacks to VML and Canvas for old browsers. It offers a whole ecosystem of different project templates. Highcharts is compatible with older browsers, too, including Internet Explorer 6.

It’s a nice solution for non-developers as it has an integrated WYSIWYG (what you see is what you get) chart, editor. Its learning curve is rather smooth and it’s been used by a number of major players, like Facebook or Microsoft—there’ve even been claims that 72 out of the 100 of the world’s largest companies have used it at some point.

In addition, you can use  SVG and/or shape generators  along with it to make your visual elements more effective.

Contrary to Recharts and D3, it’s a paid solution and carries a $1500 price tag for an unlimited commercial use license.

Under the hood, however, it feels like it was written in 2009. Recently, one of my colleagues walked me through her experience with it, and let me tell you, it wasn’t very pleasant. It works great when you’re not fiddling around under the hood, but when you want to—it’s a chore.

Highcharts GitHub Highcharts website

17. Zoomcharts

Another commercial JS data viz tool, calling itself the “world’s most interactive JavaScript charts library.” Besides reactivity, it’s focused primarily on multi-touch gestures and a native feel across all kinds of devices.

The library promises beautiful visualizations that need little code and can be easily deployed in your product.

Zoomcharts are Canvas-based, and with default settings, the library works up to twenty times faster than its SVG-based competitors using the same data and settings.

I couldn’t find the exact pricing for Zoomcharts, but I found a couple of comments that called it “expensive.” Whatever the price may be, however, in return you get amazing interactivity, multi-touch gestures, and high-caliber customer support.

Zoomcharts website Zoomcharts gallery

GitHub Stars: 11,000

Developed by the Interactive Data Lab at the University of Washington, Vega is a high-level declarative specification language for creating custom interactive visualizations. It supports D3.js under the hood and empowers expressive development with a concise, readable syntax that is both intuitive and logical.

One of the strengths of Vega lies in the declarative approach: users only specify what they want to visualize, and Vega determines how it can be rendered. This opens up the potential for complex visualizations by a non-developer or someone not highly proficient in coding. Along with this, Vega lies on top of D3, having functionalities similar to D3 but with less of the latter's syntax weight.

Vega is open-source and free, so it's a great alternative to costly solutions like Highcharts. In contrast to Highcharts, which prioritizes product development in terms of users' needs for handling data transformations and making interactive visualizations.

Works with: JSON, D3, HTML5 technologies (SVG, Canvas, WebGL)

Vega website Vega gallery

The Right Library Can Elevate Your Projects

I hope this list will help you create beautiful charts for your future projects. Good luck!