G2

Vinayak K.

Code Auditor

Small-Business (50 or fewer emp.)

10/18/2026

"Daytona Remote Sandbox: Fast Startups Without Docker Desktop"

4.5/5

What do you like best about Daytona?

What I like most about Daytona is how quickly I can spin up an isolated environment and start running AI-generated code, without having to spend time setting everything up by hand. The rapid sandbox creation, support for Python and TypeScript, and the option to save and resume environments make it especially helpful when I’m experimenting with AI agents or trying out different ideas. I also appreciate that each sandbox stays separate, so I can run code and install dependencies with less worry about impacting my main environment. Overall, Daytona lets me focus more on building and experimenting, rather than managing infrastructure. Review collected by and hosted on G2.com.

What do you dislike about Daytona?

One area I’d like to see improved is the platform’s overall transparency and flexibility as it continues to evolve. With the shift toward a closed-source production codebase, I’d appreciate clearer communication about what remains open source, how security updates are managed, and what options developers have if they want more control over their infrastructure. I’d also like better visibility into resource usage and costs, especially when running multiple sandboxes for extended periods. Improvements in these areas would make it easier to plan projects with confidence and to decide how Daytona fits into a long-term development workflow. Review collected by and hosted on G2.com.

What problems is Daytona solving and how is that benefiting you?

Daytona helps address the challenge of setting up and managing separate environments for running AI-generated code. Before using it, dealing with dependencies, container configuration, and ensuring that experimental code didn’t interfere with other projects often added extra, unnecessary work to my development process. With Daytona, I can spin up isolated sandboxes, run code programmatically, and reuse saved environments instead of rebuilding everything from scratch each time. This is particularly helpful when I’m working on AI-powered applications where code needs to be generated, tested, and executed repeatedly. Overall, it cuts down on infrastructure overhead and makes experimentation feel much smoother, so I can spend more time building features and less time managing the environments behind them. Review collected by and hosted on G2.com.