Streamlit has become a favorite among data scientists, ML engineers, and developers who want to turn Python scripts into shareable web apps—without needing full-stack web development skills. Its simplicity, speed, and Python-native syntax make it especially appealing for quick dashboards, internal tools, and data exploration interfaces.
But Streamlit isn’t the only option—and it may not be the best fit for everyone.
As 2025 unfolds, developers are increasingly exploring alternatives due to a few common reasons:
- Customization limitations: Streamlit apps are easy to build but harder to fine-tune visually or architecturally.
- Scalability concerns: Larger or more complex projects may require frameworks that support deeper component control, better state handling, or backend integration.
- Front-end flexibility: Some teams want more control over the user experience, or prefer integrating with design systems.
- Deployment preferences: Organizations with specific hosting needs or enterprise constraints may need alternatives that offer more deployment options or integrate better with CI/CD pipelines.
Whether you’re building a machine learning demo, a data visualization dashboard, or a full-stack internal tool, there are powerful Streamlit alternatives worth exploring—ranging from low-code solutions and Python-based frameworks to notebook-based tools and design-to-code platforms.
In this post, we’ll walk through the 10 best Streamlit alternatives in 2025, covering:
- Open-source tools for rapid prototyping
- Enterprise-ready frameworks with advanced customization
- No-code/low-code solutions for teams without frontend developers
- Options tailored for collaboration, ML, and real-time dashboards
Let’s dive into the best options—and help you find the right tool for your next data app or internal project.
Table of contents
1. Dash by Plotly – Best for prototype development in data science projects
Dash is an open-source Python framework developed by Plotly, designed for building analytical web applications. It excels in creating interactive dashboards with advanced data visualization capabilities.
Dash best features
- Python-first approach: Seamlessly integrates with Python data science libraries like Pandas and NumPy.
- Advanced visualizations: Leverages Plotly’s robust charting library for complex graphs.
- Customizable layouts: Offers flexibility in designing app layouts using HTML and CSS components.
- Enterprise-ready: Provides Dash Enterprise for scalable deployment and collaboration.
Dash limitations
- Steep learning curve: Requires understanding of callbacks and HTML for advanced customizations.
- Limited built-in components: May need additional development for specific UI elements.
Dash pricing
- Open-source version: Free.
- Dash Enterprise: Pricing varies based on deployment needs.
Dash ratings
- G2: 4.8/5 (30+ reviews)
2. Gradio – Best for creating machine learning app demos
Gradio is a Python library that allows developers to quickly create user-friendly web interfaces for machine learning models, facilitating easy sharing and testing.
Gradio best features
- Ease of use: Simple API to create interfaces with minimal code.
- Instant sharing: Generate shareable links for your models without deployment hassles.
- Integration with Hugging Face: Seamless connection with Hugging Face models and datasets.
- Notebook compatibility: Works well within Jupyter notebooks for rapid prototyping.
Gradio limitations
- Limited customization: Basic UI components may not suffice for complex applications.
- Short-lived links: Shared links expire after 72 hours unless hosted elsewhere.
Gradio pricing
- Open-source: Free.
- Hosting on Hugging Face Spaces: Free with limitations; premium plans available for extended features.
Gradio ratings
- G2: 4.6/5
3. Panel – Best for building interactive dashboards in Python
Panel is an open-source Python library that enables the creation of interactive web apps and dashboards using various plotting libraries.
Panel best features
- Versatility: Supports multiple plotting libraries like Bokeh, Matplotlib, and Plotly.
- Jupyter integration: Works seamlessly within Jupyter notebooks.
- Custom templates: Offers predefined templates for consistent app layouts.
- Reactive programming: Efficiently updates only the necessary components upon user interaction.
Panel limitations
- Deployment complexity: Requires setting up a server for hosting applications.
- Learning curve: May be challenging for beginners unfamiliar with the underlying plotting libraries.
Panel pricing
- Open-source: Free.
Panel ratings
- G2: 4.5/5
4. Anvil – Best for advanced app customizations
Anvil is a platform that allows developers to build full-stack web applications entirely in Python, eliminating the need for traditional web development languages.
Anvil best features
- Full-stack development: Write both frontend and backend code in Python.
- Drag-and-drop interface: Simplifies UI design with a visual editor.
- Built-in database: Provides a built-in database for quick data storage and retrieval.
- Serverless hosting: Offers hosting solutions without server management.
Anvil limitations
- Performance constraints: May not be suitable for high-performance applications.
- Limited community support: Smaller user base compared to other frameworks.
Anvil pricing
- Free tier: Limited features.
- Paid plans: Start at $15/month with additional features and hosting options.
Anvil ratings
- G2: 4.4/5
5. Shiny for Python – Best for prototyping web applications
Shiny, originally developed for R, now offers a Python version that enables the creation of interactive web applications with reactive programming.
Shiny best features
- Reactive programming model: Automatically updates outputs when inputs change.
- Integration with Python libraries: Works well with libraries like Pandas and Plotly.
- Simplified syntax: Easy to learn for users familiar with Python.
Shiny limitations
- Limited scalability: May not be ideal for large-scale applications.
- Fewer resources: Smaller community and fewer tutorials compared to other frameworks.
Shiny pricing
- Open-source: Free.
Shiny ratings
- G2: 4.3/5
6. Deepnote – Best for real-time collaboration on code
Deepnote is a collaborative data science notebook that combines the capabilities of Jupyter notebooks with real-time collaboration features.
Deepnote best features
- Real-time collaboration: Multiple users can work simultaneously on the same notebook.
- Version control: Built-in Git integration for tracking changes.
- Cloud-based: Access notebooks from anywhere without local setup.
- Integration with data sources: Connects with databases and data warehouses.
Deepnote limitations
- Limited offline access: Requires internet connectivity for full functionality.
- Pricing for teams: Advanced collaboration features may require paid plans.
Deepnote pricing
- Free tier: Basic features.
- Pro plan: Starts at $12/user/month.
Deepnote ratings
- G2: 4.7/5
7. Mercury Framework – Best for Jupyter Notebook users
Mercury is a framework that transforms Jupyter notebooks into interactive web applications without requiring any frontend development.
Mercury best features
- Notebook conversion: Easily turn notebooks into web apps with interactive widgets.
- Parameterization: Add input widgets to control notebook parameters.
- Static export: Generate static HTML reports from notebooks.
Mercury limitations
- Limited interactivity: Not suitable for highly dynamic applications.
- Deployment setup: Requires additional configuration for hosting.
Mercury pricing
- Open-source: Free.
Mercury ratings
- G2: 4.2/5
8. Taipy – Best for data visualization
Taipy is a Python library designed to build production-ready applications for data science and machine learning projects.
Taipy best features
- Scalability: Handles large datasets efficiently.
- Multi-user support: Manages various user profiles and access levels.
- Workflow management: Simplifies the creation of data pipelines and workflows.
Taipy limitations
- Learning curve: May require time to understand its architecture.
- Community size: Smaller community compared to other frameworks.
Taipy pricing
- Open-source: Free.
Taipy ratings
- G2: 4.3/5
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9. Datalore – Best for AI code assistance
Datalore by JetBrains is an intelligent web application for data analysis and visualization, combining the power of Jupyter notebooks with collaborative features.
Datalore best features
- Smart coding assistance: Offers code completion and error detection.
- Collaboration: Share notebooks and collaborate in real-time.
- Integrated tools: Includes tools for data visualization and machine learning.
Datalore limitations
- Performance: May experience latency with very large datasets.
- Pricing: Advanced features may require a subscription.
Datalore pricing
- Free tier: Limited features.
- Professional plan: Starts at $10/month.
Datalore ratings
- G2: 4.6/5
10. PixelFree Studio – Best for Figma users
PixelFree Studio is a design-to-code platform that allows users to convert Figma designs into responsive web applications.
PixelFree Studio best features
- Design integration: Seamlessly imports Figma designs.
- Code generation: Automatically generates clean, responsive code.
- Customization: Offers tools to fine-tune the generated code.
PixelFree Studio limitations
- Limited backend support: Focuses primarily on frontend development.
- Learning curve: May require time to understand the platform’s features.
PixelFree Studio pricing
- Free tier: Basic features.
- Pro plan: Pricing varies based on requirements.
PixelFree Studio ratings
- G2: 4.5/5
Summary
| Tool | Best For | Pricing | G2 Rating |
| Dash by Plotly | Prototype development in data science | Free/Open-source | 4.8/5 |
| Gradio | Creating machine learning app demos | Free/Open-source | 4.6/5 |
| Panel | Building interactive dashboards in Python | Free/Open-source | 4.5/5 |
| Anvil | Advanced app customizations | Free/$15+/month | 4.4/5 |
| Shiny for Python | Prototyping web applications | Free/Open-source | 4.3/5 |
| Deepnote | Real-time collaboration on code | Free/$12+/month | 4.7/5 |
| Mercury Framework | Jupyter Notebook users | Free/Open-source | 4.2/5 |
| Taipy | Data visualization | Free/Open-source | 4.3/5 |
| Datalore | AI code assistance | Free/$10+/month | 4.6/5 |
| PixelFree Studio | Figma users | Free/Varies | 4.5/5 |
Each of these alternatives offers unique features catering to different needs. Depending on your specific requirements—be it rapid prototyping, advanced customization, or collaborative development—you can choose the tool that best fits your project.
If you need further assistance in selecting the right tool for your specific use case, feel free to ask!
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