Top 5 Open-Source Chart Libraries for User-Facing Analytics

Top 5 Open-Source Chart Libraries for User-Facing Analytics

January 22, 2024

When building user-facing analytics, the build versus buy debate is one you’ll likely encounter. Whether you're embedding analytics into your application or enhancing user interactions with insightful data visualizations, the balance of time-to-market versus control and flexibility is one you’ll want to optimize for. In this post, we’ll run you through the top 5 open-source libraries and make the case for why Vizzly provides the best of both worlds as far as time-to-market and control over user experience when embedding analytics.


Chart.js is a versatile and widely-used open-source charting library that seamlessly integrates into user interfaces. With a simple API, developers can create responsive and interactive charts, including line charts, bar charts, and radar charts. Its ease of use make it a good choice for embedding analytics for user-facing dashboards.

  • Ease of Integration: Seamless integration into user interfaces.
  • Responsive design: charts adapt well to different screen sizes.
  • Interactive elements: offers tooltips and animations for enhanced user engagement.
  • Community support: benefits from a large and active community.

  • Limited Complexity: May struggle with extremely complex visualizations.
  • Configuration Overhead: Limited customization options for some developers.
  • Learning Curve: Advanced features may require time investment.
  • Dependency on Canvas: Relies on HTML5 Canvas, limiting options for some projects.


For those seeking maximum customization and control over data visualizations, D3.js stands out. This JavaScript library allows developers to bind data to the Document Object Model (DOM), enabling the creation of dynamic and data-driven visualizations. While it has a steeper learning curve, the flexibility it offers makes it an interesting choice for building user-facing analytics applications. That said, you will have a lot of work to do!

  • Unparalleled customization: developers to create highly tailored and unique visualizations.
  • Control over data binding: developers can bind data to the DOM, for more dynamic data viz.
  • Flexibility: The library offers a high degree of freedom for complex user-facing dashboards.

  • Steep learning curve: considerably more complex than other charting libraries or frameworks.
  • Development time: time-to-market is significant, as you’d expect from a low-level library.
  • Limited defaults: you get much less bang for your buck from the outset.


Plotly is an open-source charting library that’s great for building complex visualizations, often used in ML-based data products. With support for a wide range of chart types, including scatter plots, heatmaps, and choropleths, Plotly is a good option for those looking to create sophisticated user-facing analytics for data science projects.

  • Complex visualizations: well-suited for building complex viz e.g. for ML-based products.
  • Chart type selection: choose from a diverse set of chart types to suit deep analytical requirements.
  • Interactivity: offers off-the-shelf interactive features for data exploration
  • Limited customization: limited for developers seeking highly tailored visualizations.
  • Can be overkill if you don't need geospatial or clustering visualizations; there may be better options.
  • License considerations: while open-source, licensing is needed for most use cases.


Tremor is a new open-source React library. Just like Chart.js, it's high-level but offers charting components as well as other components one would need to build a basic user-facing analytics dashboard. Good for simple user-facing dashboards and has a growing community.

  • Provides more than just data visualization components; you also get filter components, for example.
  • The library is aesthetically pleasing - something that can't be said about many chart libraries.
  • Community: growing Slack community of people building simple user-facing dashboards.
  • The product is highly opinionated; developers have less control than alternatives.
  • React-only. Angular, Vue and Svelte users will need to find alternatives.


Streamlit is a little different from the others. It's a Python library designed for creating web apps with minimal effort, focusing on simplicity and efficiency. Although you may not build robust user-facing analytics with Streamlit, it's terrific for building data web apps, especially if you're a Pythonista who lacks frontend development experience.

  • Rapid prototyping: developers to create interactive web apps with minimal code.
  • Pythonic Syntax: accessible to developers with varying levels of expertise.
  • Real-time interaction: suitable for applications requiring dynamic user engagement.
  • Targeted towards data scientists, not really used for web app development.
  • Limited customization but highly functional experience.
  • Dependency on Python.

Vizzly - The All-in-One User-Facing Analytics Solution

For developers looking for a comprehensive solution to user-facing analytics, Vizzly presents itself as a compelling alternative to open-source chart libraries. Unlike other embedded analytics solutions, Vizzly is highly extensible to give engineering teams max control over the analytics experience.

Why Choose Vizzly for User-Facing Analytics:


Of course, time-to-market is a huge reason why any fast-moving company would opt for a low-code solution. For example, with Vizzly, you get a query engine (no need for API development), SDKs to help with permissioning, a no-code dashboard builder, and a range of developer tools.


Vizzly comes with a bunch of developer-centric features. We understand low-code can only get you so far! With Vizzly, you can override CSS objects, dashboard components and soon you’ll be able to inject custom data visualization using the Plugin API.


Vizzly offers a JS services dashboard for programmatic dashboard building, callback functions for creating custom click events, and there is so much nuance in user-facing analytics. Vizzly handles that nuance and other complexities super well.

Ultimately, with Vizzly, you get longevity. Sure, you get your user-facing dashboard to market quickly, but down the line, when you want to extend or improve the solution, Vizzly’s configurability gives you immense optionality. For example, maybe you want to offer custom reporting or self-serve dashboards to enterprise users in the future. With Vizzly, it'd be a flick of a switch to move between states.

Check out our blog here on more detail why people choose Vizzly over open-source chart libraries.

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