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D3.js VS Streamlit

Compare D3.js VS Streamlit and see what are their differences

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D3.js logo D3.js

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Streamlit logo Streamlit

Turn python scripts into beautiful ML tools
  • D3.js Landing page
    Landing page //
    2023-07-11

D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.

D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of official and community-developed modules.

  • Streamlit Landing page
    Landing page //
    2023-10-07

D3.js features and specs

  • Powerful Visualization
    D3.js allows for the creation of highly customized and interactive data visualizations, harnessing the full power of web standards like SVG, Canvas, and HTML.
  • Data Binding
    It offers robust support for data-driven transformations and binding, enabling intuitive connections between data sets and DOM elements.
  • Community and Ecosystem
    A large and active community contributes to tutorials, plugins, and tools, which can significantly simplify the development process.
  • Flexibility
    D3.js is highly flexible, providing low-level manipulation capabilities without being tied to any specific chart types or patterns.
  • Performance
    It is highly optimized for performance, allowing for efficient rendering of complex visualizations even with large data sets.

Possible disadvantages of D3.js

  • Steep Learning Curve
    D3.js has a steep learning curve due to its low-level nature and requires a solid understanding of JavaScript, DOM manipulation, and data concepts.
  • Complexity
    Creating complex visualizations can be time-consuming and require a significant amount of custom code, making it less approachable for quick, simple tasks.
  • Browser Compatibility
    Although widely supported, some D3.js features may have inconsistent behavior across different browsers, requiring additional testing and debugging.
  • Documentation
    While extensive, D3.js documentation can be challenging for beginners to navigate and understand, causing misunderstandings and slower development times.
  • Dependency Management
    The library itself is modular, but managing dependencies and integrating D3.js with other JavaScript frameworks or libraries can sometimes be problematic.

Streamlit features and specs

  • Ease of Use
    Streamlit's API is extremely intuitive and easy to learn, which makes it accessible for developers of varying experience levels. The simplicity allows for rapid development and less time spent on complex front-end coding.
  • Interactive Widgets
    It provides a set of interactive widgets that make it simple to add complex functionalities like sliders, buttons, and file uploaders to your application with minimal code.
  • Real-time Feedback
    Streamlit supports real-time data updates, allowing users to see changes instantly. This is particularly useful for data analysis and machine learning applications where live data visualization is crucial.
  • Integration with Machine Learning Libraries
    Streamlit integrates seamlessly with popular machine learning libraries like TensorFlow, PyTorch, and scikit-learn, making it a great tool for showcasing machine learning models and results.
  • Open Source
    Being an open-source project, Streamlit is free to use and comes with the support and contributions of an active community. This means continuous improvements and a wealth of shared resources.

Possible disadvantages of Streamlit

  • Limited Customization
    Streamlit offers limited customization options compared to traditional web frameworks. This can be a hindrance if you need a highly customized UI/UX for your application.
  • Performance Issues
    For more complex or resource-intensive applications, Streamlit may suffer from performance drawbacks. It is not designed for high-performance computing out of the box.
  • Scalability
    Streamlit is not well-suited for large-scale applications requiring major backend architecture or for scenarios demanding high scalability and concurrency.
  • Limited Widget Style Options
    The styling and customization options for widgets are somewhat limited, meaning your application's look and feel might be more constrained compared to using other front-end frameworks.
  • Deployment Complexity
    While Streamlit provides some deployment options, deploying Streamlit apps in a production environment can sometimes require additional effort and knowledge, especially for those unfamiliar with web deployment practices.

Analysis of D3.js

Overall verdict

  • Yes, D3.js is a highly regarded library for data visualization in the web development community.

Why this product is good

  • Flexibility: D3.js provides incredible flexibility in creating complex and interactive visualizations with web standards (SVG, HTML, and CSS).
  • Customization: It allows for high levels of customization, which lets developers create unique and detailed visualizations tailored to their specific needs.
  • Community and Ecosystem: D3.js has a large, active community and a rich ecosystem of plugins and extensions conducive to learning and integration.
  • Data Binding: Offers powerful ways to manipulate documents based on data; the data-driven approach simplifies dynamic interaction creation.
  • Performance: Efficiently manipulates DOM elements and performs well with large datasets if used correctly.

Recommended for

  • Data Scientists and Analysts looking to create custom, interactive visualizations.
  • Web Developers who need to incorporate complex data visualizations into applications.
  • Educators and Researchers presenting data in an engaging way.
  • Anyone needing to build bespoke visualizations that are not possible with off-the-shelf solutions.

Analysis of Streamlit

Overall verdict

  • Overall, Streamlit is well-regarded for its ease of use, speed of development, and ability to create clean and professional-looking applications without in-depth web development knowledge. It provides a seamless bridge between complex data analysis and user-friendly presentation, which can be highly beneficial for a wide range of use cases.

Why this product is good

  • Streamlit is a popular choice for quickly building and deploying data applications and interactive dashboards with minimal code. It is designed to be user-friendly, allowing data scientists and engineers to transform their scripts into shareable web apps. It supports real-time updates, is highly customizable, and integrates well with Python libraries like NumPy, Pandas, and Matplotlib, making it an attractive option for many developers working within the Python ecosystem.

Recommended for

    Streamlit is ideal for data scientists, analysts, and developers looking to rapidly prototype and deploy data-driven applications. It is recommended for those who prioritize simplicity, quick deployment, and seamless integration with Python code. Individuals or teams interested in building dashboards, ML model sharing platforms, or interactive reports will find Streamlit particularly useful.

D3.js videos

+ Add

Data Visualization with D3.js - Full Tutorial Course

More videos:

  • Review - Let's learn D3.js - D3 for data visualization (full course)

Streamlit videos

+ Add

My thoughts on web frameworks in Python and R (PyWebIO vs Streamlit vs R Shiny)

More videos:

  • Review - 1/4: What is Streamlit
  • Tutorial - How to Build a Streamlit App (Beginner level Streamlit tutorial) - Part 1

Category Popularity

0-100% (relative to D3.js and Streamlit)

D3.js

Streamlit

Charting Libraries
100 100%
Charting Libraries
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
Productivity
0 0%
Productivity
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare D3.js and Streamlit

D3.js Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
Depending on your requirements, the best JavaScript library is D3.js, as it’s by far the most customizable. However, it’s also really complex and difficult to master. Plus, it’s not as compatible with TypeScript as it is with JavaScript, which can be off-putting for some developers. If you’d prefer a less complex library that you can use with TypeScript, ECharts, and...
Source: embeddable.com
15 JavaScript Libraries for Creating Beautiful Charts
When we think of charting today, D3.js is the first name that comes up. Being an open source project, D3.js definitely brings many powerful features that were missing in most of the existing libraries. Features like dynamic properties, Enter and Exit, powerful transitions, and syntax familiarity with jQuery make it one the best JavaScript libraries for charting. Charts in...
Source: www.sitepoint.com
Top 20 Javascript Libraries
D3 stands for Data-Driven Documents. With D3, you can apply data-driven transformations to DOM objects. The keyword with D3 is ‘data-driven,’ which means documents are manipulated depending on the data received. Data can be received in any format and bound with DOM objects. D3 is very fast and supports dynamic behavior for animation and interactions. There are plenty of...
Source: hackr.io
20+ JavaScript libraries to draw your own diagrams (2022 edition)
D3.js is a JavaScript library for manipulating documents based on data. Right now, I would say is the most popular library of its kind.
Source: modeling-languages.com
15 data science tools to consider using in 2021
Another open source tool, D3.js is a JavaScript library for creating custom data visualizations in a web browser. Commonly known as D3, which stands for Data-Driven Documents, it uses web standards, such as HTML, Scalable Vector Graphics and CSS, instead of its own graphical vocabulary. D3's developers describe it as a dynamic and flexible tool that requires a minimum amount...
Source: searchbusinessanalytics.techtarget.com

Streamlit Reviews

We have no reviews of Streamlit yet.
Be the first one to post

Social recommendations and mentions

Streamlit might be a bit more popular than D3.js. We know about 210 links to it since March 2021 and only 167 links to D3.js. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

D3.js mentions (167)

  • IO Devices and Latency
    Do you mean something for data visualization, or tricks condensing large data sets with cursors? https://d3js.org/ Best of luck =3. - Source: Hacker News / 3 months ago
  • 2024 Nuxt3 Annual Ecosystem Summary🚀
    Document address: D3.js Official Document. - Source: dev.to / 6 months ago
  • 100+ Must-Have Web Development Resources
    D3.js: One of the most popular JavaScript visualization libraries. - Source: dev.to / 8 months ago
  • What are npm Peer Dependencies and how to use them?
    A Dependency is an npm package that our code depends on in order to be able to run. Some popular packages that can be added as dependencies are lodash, D3, and chartjs. - Source: dev.to / 8 months ago
  • Introducing RacingBars 📊
    RacingBars is an open-source, light-weight (~45kb gzipped), easy-to-use, and feature-rich javascript library for bar chart race, based on D3.js. - Source: dev.to / 10 months ago
View more

Streamlit mentions (210)

  • Predictive Maintenance Systems for Cleaning Robots: Boosting Efficiency Through Smart Tech
    Use Streamlit to visualize and test predictions interactively:. - Source: dev.to / 1 day ago
  • Build Code-RAGent, an agent for your codebase
    The only thing left to do then was to build something that could showcase the power of code ingestion within a vector database, and it immediately clicked in my mind: "Why don't I ingest my entire codebase of solved Go exercises from Exercism?" That's how I created Code-RAGent, your friendly coding assistant based on your personal codebases and grounded in web search. It is built on top of GPT-4.1, powered by... - Source: dev.to / about 1 month ago
  • How AI is Transforming Front-End Development in 2025!
    Streamlit.io: Great documentation and reusable components to integrate with your AI application for rapid python front-end AI development. - Source: dev.to / about 1 month ago
  • Querying DynamoDB with Natural Language Using MCP
    The agent uses MCP to translate this into a DynamoDB query. Then, using Streamlit UI, results are returned in a structured format, making it easy to use. - Source: dev.to / 3 months ago
  • Can I run this LLM?
    It's powered by something called "Streamlit" (https://streamlit.io). > A faster way to build and share data apps Website doesn't even load for me. I don't even know what to say...welcome to web dev 2025 edition. - Source: Hacker News / 3 months ago
View more

What are some alternatives?

When comparing D3.js and Streamlit, you can also consider the following products

Chart.js - Easy, object oriented client side graphs for designers and developers.

Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.

Plotly - Low-Code Data Apps

Recut - Edit silence out of videos automatically

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

FastAPI - FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

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