Streamlit has become a popular choice for building interactive dashboards and applications using Python. However, it often requires substantial coding, making it more suitable for technically proficient users. Several alternatives offer similar capabilities with added features like AI assistance and more user-friendly interfaces. Here are the seven best Streamlit alternatives for 2024, starting with Deepnote.
Deepnote
Deepnote changes how data science teams collaborate, with a robust, simple platform designed to meet the needs of modern data projects. Let us show you what makes Deepnote an essential tool for data professionals all over the world.
Deepnote’s features
- Real-time collaboration: Deepnote enables simultaneous editing of notebooks by multiple users. This real-time collaboration feature ensures that team members can work together seamlessly, enhancing productivity and fostering a collaborative environment.
- Deepnote AI: The platform integrates powerful AI capabilities such as intelligent code suggestions, automated data cleaning, natural language querying, and smart visualizations. These AI-driven tools significantly accelerate the data analysis, allowing users to focus on deriving insights rather than mundane tasks.
- Custom environments: Users can customize their computational environment by specifying the necessary libraries and dependencies. This flexibility ensures each project can operate within a tailored setup, optimizing performance and compatibility.
- Integrations with other data platforms: Deepnote offers seamless integration with many data sources, including databases and data warehouses. This integration capability allows users to connect to and query their data without leaving the Deepnote interface, simplifying the data workflow.
- Cloud computing: By leveraging cloud computing, Deepnote provides scalable computational resources that can handle large datasets and complex algorithms anywhere you are. This ensures that projects are not constrained by local hardware limitations and can scale as needed.
- Data apps: Deepnote allows users to build and deploy interactive data applications directly from their notebooks. This feature facilitates the sharing of insights and results, making it easier for teams to collaborate and stakeholders to understand the data.
- Interactive visualizations: The platform includes robust tools for creating interactive visualizations, enabling users to explore and analyze their data visually. These visualizations help uncover patterns and insights that might be missed in raw data.
- No-code/low-code features: Deepnote’s no-code/low-code features enable users to perform complex data tasks with minimal programming. This makes advanced data analysis accessible to a broader range of users, including those without extensive coding experience.
Why choose Deepnote?
Deepnote stands out with real-time collaboration, rich AI features, customizable environments, seamless integrations, and cloud computing capabilities. Whether you want to train the next generation of Artificial intelligence, analyze new trends in the world of data, explore yet-unknown science, or make a cool app to track your coffee routine, Deepnote got you covered with the tools necessary to enhance productivity, streamline workflows, and achieve success in your data-driven projects.
Dash by Plotly
Dash by Plotly is a Python framework for building analytical web applications. It’s ideal for creating complex dashboards with interactive elements.
Key features
- Rich interactive components: Use pre-built components to create interactive applications.
- Integration with plotly: Leverage Plotly’s powerful visualization library for creating complex charts and graphs.
- Customization: Customize the look and feel of your applications extensively.
Why choose Dash?
Dash is perfect for users who need to create highly customizable and interactive dashboards with advanced visualization capabilities.
Voila
Voila turns Jupyter notebooks into standalone web applications, making it easy to share interactive data visualizations and dashboards.
Key features
- Jupyter integration: Convert Jupyter notebooks into web applications effortlessly.
- Interactive widgets: Utilize Jupyter’s interactive widgets to create rich user interfaces.
- Easy deployment: Deploy applications with minimal setup.
Why choose Voila?
Voila is ideal for users who are already comfortable with Jupyter notebooks and want a straightforward way to turn them into interactive web applications.
Gradio
Gradio is a Python library that allows you to create user interfaces for machine learning models and data science workflows quickly.
Key features
- Simple UI creation: Build user interfaces with minimal code.
- Interactive demos: Create demos for machine learning models that users can interact with.
- Easy integration: Integrate with various Python libraries and frameworks.
Why choose Gradio?
Gradio is perfect for creating interactive demos and user interfaces for machine learning models with minimal effort.
Shiny for Python
Originally designed for R, Shiny now offers a Python version, allowing users to build interactive web applications directly from Python scripts.
Key features
- Interactive UI elements: Create dynamic web applications with a wide range of UI components.
- Reactive programming: Use reactive programming to make applications responsive to user inputs.
- Ease of use: Simplified syntax for building web applications.
Why choose Shiny?
Shiny for Python is great for users familiar with Shiny in R or those looking for a straightforward way to create interactive web applications in Python.
Tableau
Tableau is a leading data visualization tool that helps users convert raw data into actionable insights through intuitive and interactive dashboards. It’s known for its powerful visualization capabilities and ease of use.
Key features
- Interactive dashboards: Create dynamic and interactive dashboards that allow for deep data exploration.
- Ease of use: Tableau’s user-friendly interface makes it accessible for users of all skill levels.
- Strong community support: Benefit from a large and active user community, providing resources and shared knowledge.
- Integration with multiple data sources: Tableau can connect to a wide variety of data sources, ensuring flexibility in data analysis.
Why choose Tableau?
Tableau is perfect for users who prioritize powerful data visualization and need a tool that offers intuitive and interactive dashboards to uncover insights quickly.
Datalore
Datalore is an intelligent web application for data analysis and visualization by JetBrains. It combines the power of Jupyter Notebooks with JetBrains’ intelligent coding assistance.
Key features
- Intelligent code assistance: Benefit from smart code completion, inspections, and refactorings.
- Collaborative features: Share and work on notebooks with your team.
- Interactive visualizations: Create rich, interactive visualizations within your notebooks.
Why choose Datalore?
Datalore is ideal for those who want the enhanced coding experience provided by JetBrains’ intelligent tools combined with the collaborative and interactive features of a modern data science notebook.
Summary
While Streamlit is a powerful tool for building interactive dashboards, it can be limiting for those who seek more user-friendly, collaborative, and AI-driven alternatives. Deepnote leads the pack with its real-time collaboration, AI-powered features, and ease of use, making it an excellent choice for data analysts. Other alternatives like Dash, Voila, and Gradio offer unique capabilities that cater to different needs, ensuring that there’s a tool here to meet your specific requirements in 2024.