⚡ Data Science

Data science platforms and tools help users build, test, and share data models, visualizations, and experiments.

They often include features such as cloud-based coding environments, interactive notebooks, built-in datasets, collaboration tools, and support for machine learning and artificial intelligence workflows.

According to our data, data science technologies are detected on 0.02% of all websites.
97.1% of these sites use only one data science technology, 2.7% use two, and 0.2% use three or more simultaneously.

⭐ Most Popular in 2026

The following chart shows the leading data science technologies on the web in 2026, based on market share.

The most popular is Hugging Face with an impressive share of 43.7%, followed by Quarto with 21.9% and Jupyter Notebook with 12.1%.

Hugging Face 43.7%
Quarto 21.9%
Jupyter Notebook 12.1%
Google Colab 9.9%
Kaggle 5.9%
Anvil 4.5%
Streamlit 3.6%
Dash 1.4%

You can also drill down by country:

✨ Best Data Science Technologies

Below is a more detailed list of 8 data science technologies we track, ranked by their market share.

Rank	Name	Market share
1	Hugging Face New York, United States A machine learning and data science platform and community that helps users build, deploy and train machine learning models.	43.7%
2	Quarto Boston, Massachusetts, United States An open-source scientific and technical publishing system based on Markdown that allows users to write in plain-text Markdown or work with Jupyter notebooks and embed executable code in Python, R, Julia, or Observable JS. FreeOpen source	21.9%
3	Jupyter Notebook A web application that allows you to execute code, visualize its output (such as plots, images, tables, etc.), and write explanations - all in a single notebook file.	12.1%
4	Google Colab Mountain View, California, United States A free Jupyter Notebook hosted environment from Google.	9.9%
5	Kaggle Mountain View, California, United States A platform for data science and machine learning that offers a variety of resources, including datasets, code repositories, and tools for building and deploying machine learning models.	5.9%
6	Anvil Cambridge, United Kingdom A platform for building full-stack data applications for the web in Python. Free$15+/month	4.5%
7	Streamlit San Francisco, California, United States An open-source Python framework for data scientists and AI/ML engineers to deliver dynamic data apps with only a few lines of code. FreeOpen source	3.6%
8	Dash Montreal, Quebec, Canada An original low-code framework for rapidly building data applications in Python, built on top of Plotly.js, React, and Flask. FreeOpen source$$$	1.4%

Data is based on the analysis of 3,333,506 websites.
Statistics were last calculated on April 2, 2026.
For details, see our methodology and disclaimer.