Two leading ai engineering tools, scored head to head so you can see which one wins on the metrics that matter to you.
The Visual No Code App Builder – Now Powered By AI
Adalo is the visual no-code AI app builder that allows users to design, build, and publish custom database-driven apps without writing code.
The AI project partner inside your notebook
Runcell is the Jupyter-native AI agent for domain experts running real, multi-week ML and data projects.
Adalo leads 4 of 6 rounds
Adalo leads on monthly traffic, domain rating and feature coverage. Runcell is stronger on traffic growth.
The details
Adalo
Worldwide, desktop only
Runcell
Top regions
Adalo
Runcell
No regional data available.
What is Adalo?
Adalo is a visual no-code AI app builder that allows users to design, build, and publish custom database-driven apps without writing code.
Who is Adalo for?
Adalo is primarily for individuals and businesses looking to build custom applications, such as delivery apps, eCommerce platforms, and order tracking systems, without needing coding skills.
What can I do with Adalo?
With Adalo, you can generate multi-screen apps using plain language descriptions, visually design your app layout on a multi-screen canvas, and publish your app to iOS, Android, and web platforms from a single project.
How much does Adalo cost?
Adalo offers a freemium pricing model, which includes a free plan with no credit card required, a hosted Postgres database, and 500 records with no time limit.
How is Adalo different from alternatives?
Adalo differentiates itself by combining visual app design with AI capabilities, allowing users to create functional apps quickly and easily without coding, while also providing built-in database management and multi-platform deployment.
Can I use runcell with Jupyter Notebook?
**No**, runcell currently only supports **JupyterLab 4.4.0+**. The classic Jupyter Notebook interface is not supported. To switch from Jupyter Notebook to JupyterLab: ``` pip install jupyterlab jupyter lab # instead of jupyter notebook ```
What's the difference between the installation methods?
- **pip from PyPI** (recommended): Automatic dependency management, always latest version - **conda + pip**: Best for conda users, maintains environment isolation - **uv**: Fastest installation, good for CI/CD environments - **Manual wheel**: For offline installations or specific version requirements
Why use pip within conda environments?
While conda is excellent for environment management, pip provides better compatibility for Python wheel files and ensures proper installation of JupyterLab extensions.
How do I verify the installation worked?
1. Start JupyterLab: `jupyter lab` 2. Check the right sidebar for the runcell extension 3. The extension should appear as an icon in the sidebar 4. Click on it to access runcell functionality
What is WebGL fluid simulation?
Stronger on monthly traffic, domain rating and feature coverage.
Stronger on traffic growth.
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Framer
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