Daytona vs JupyterLab
Daytona
daytona.io
JupyterLab
jupyter.orgSide by side
| Figure | Daytona | JupyterLab |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 9 | 1 |
| Spec score · Coding Playgrounds | 9.2 (#8) | 9.1 (#9) |
| Documentation depth | The official docs cover platform concepts, sandbox classes, agent tools, human tools, webhooks, security, observability, deployments, SDK references and CLI usage. | Documentation includes user guides, developer material, an extension migration guide, API reference, security guidance and a detailed changelog. |
| Founded | 2023 | 2014 |
| Rating on G2 | 4.3 out of 5 from 24 reviews. | 4.5 out of 5 from 3 reviews |
| Self-hosting | Bring-your-own-compute custom regions let organizations attach their own runner machines and control locality and infrastructure. | JupyterLab is installed and launched locally with the `jupyter lab` command, so organizations can operate it on their own computers or servers. |
| What it does | Daytona provides secure, elastic infrastructure for executing AI-generated code inside isolated sandboxes. | JupyterLab is a web-based environment for interactive and reproducible computing with notebooks, terminals, text editors, file browsing and rich outputs. |
Plans
Daytona
- Pay-as-you-goPrice not published
- Free compute creditFree
- Start-upsFree
- StorageFree
- Memory$0.02 a month
- Compute vCPU$0.05 a month
- Windows compute$0.09 a month
- EnterprisePriced on request
- Pay as you goPrice not published
In their own words
Daytona
Daytona provides a secure, elastic runtime for executing AI-generated code and agent workflows. Its homepage states that sandbox creation takes under 90ms, and Daytona describes runtime isolation for code execution. Programmatic controls cover processes, file-system operations, Git integration, and built-in language-server support. SDK examples or interfaces are shown for Python, TypeScript, Ruby, Go, and Java. Listed uses include AI evaluations, code interpreter workloads, coding agents, and data analysis. The product's listed environments include API, Linux, macOS, self-hosted, web, and Windows; its CLI documentation supports macOS, Linux, and Windows. Documentation lists Claude, Cursor, and Windsurf as supported agents. Network options include IP and domain allow lists, outbound blocking, and chained proxies. Organization-scoped secrets are encrypted at rest and injected as placeholders into sandboxes, with plaintext substituted only for allowed HTTPS hosts. Daytona has free offerings and usage-based pricing; compute, memory, storage, and Windows rates are listed, while Enterprise pricing requires contacting sales.
JupyterLab
JupyterLab is a web-based environment for interactive work with notebooks, code and data. Its workspace brings notebooks, text editors, terminals and custom components together in tabs and splitters. Code consoles act as scratchpads, and kernel-backed documents can run code in files such as Markdown, Python, R and LaTeX. It supports the .ipynb format used by classic Jupyter Notebook, and can view and edit formats including Markdown, images, CSV, JSON, HTML, LaTeX and PDF. Visualization libraries include matplotlib and Plotly; interactive plots or widgets may require additional packages. Extensions can add themes, viewers, editors, output renderers and interface controls, but can execute code in the browser, server and kernel, so only trusted extensions are advised. Real-time collaboration can be enabled with jupyter_collaboration. JavaScript and HTML outputs from notebooks created elsewhere remain hidden until the notebook is trusted. JupyterLab is free, open-source software under a modified BSD license, installed with pip or via a Homebrew command for macOS and Linux. It runs on Linux, macOS, the web and self-hosted systems.