--- title: "daytona vs eval-view" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/daytonaio-daytona-vs-hidai25-eval-view" tools: ["daytonaio-daytona", "hidai25-eval-view"] --- # daytona vs eval-view *GraphCanon updated Jul 11, 2026* ## Verdict Pick daytona when requirements: While creating and managing sandboxes in Daytona, users require an API key to authenticate their requests.; pick eval-view when tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. [daytona](https://daytona.io) reports 72k GitHub stars, 5.7k forks, and 444 open issues, last pushed Jul 9, 2026. [eval-view](https://evalview.com) has 122 stars, 21 forks, and 6 open issues, last pushed Jul 3, 2026. Figures are from public GitHub metadata via [daytona's repository](https://github.com/daytonaio/daytona) and [eval-view's repository](https://github.com/hidai25/eval-view). | | [daytona](/tools/daytonaio-daytona.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Tagline | Secure and Elastic Infrastructure for Running AI-Generated Code | Regression testing for AI agents. Snapshot behavior,diff tool calls,catch regressions in CI. Works with LangGraph, CrewAI, OpenAI, Anthropic. | | Stars | 72,233 | 122 | | Forks | 5,663 | 21 | | Open issues | 444 | 6 | | Language | - | Python | | Adopt for | Daytona, known for its secure and elastic infrastructure tailored specifically to run AI-generated code, stands distinct in the developer tools landscape. | - | | Persona | - | - | | Runtime | - | - | | License | The license details for Daytona are unknown at present. | Apache-2.0 | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [daytona](/tools/daytonaio-daytona.md) | [eval-view](/tools/hidai25-eval-view.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 8d | | Open issues (now) | 444 | 6 | | Owner type | Organization | User | | Security scan | No lockfile | 1 medium (1 medium) | | Full report | [trust report](/tools/daytonaio-daytona/trust.md) | [trust report](/tools/hidai25-eval-view/trust.md) | ## Decision facts: daytona - **Pricing:** unknown - **Requirements:** While creating and managing sandboxes in Daytona, users require an API key to authenticate their requests. - **Adopt for:** Daytona, known for its secure and elastic infrastructure tailored specifically to run AI-generated code, stands distinct in the developer tools landscape. - **License detail:** The license details for Daytona are unknown at present. ## Choose when ### Choose daytona if… - Requirements: While creating and managing sandboxes in Daytona, users require an API key to authenticate their requests.. - Tags unique to daytona: agentic-workflow, ai-runtime, ai-sandboxes, code-execution. - When your project requires running AI-generated code securely and you need an on-demand scalable environment that adjusts automatically based on demand. ### Choose eval-view if… - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. - Also covers LLM Frameworks. - eval-view ships Docker support for self-hosted deployment. ## When NOT to use daytona - Avoid using Daytona if you have strict requirements for the programming languages it supports, since this information is currently unknown. - Daytona might not be suitable if your development workflow does not require API access or an online dashboard, as its user interface and API integration are key components. ## When NOT to use eval-view - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between daytona and eval-view? daytona: Secure and Elastic Infrastructure for Running AI-Generated Code. eval-view: Regression testing for AI agents. Snapshot behavior,diff tool calls,catch regressions in CI. Works with LangGraph, CrewAI, OpenAI, Anthropic.. See the comparison table for live GitHub stats and shared categories. ### When should I choose daytona over eval-view? Choose daytona over eval-view when Requirements: While creating and managing sandboxes in Daytona, users require an API key to authenticate their requests.; Tags unique to daytona: agentic-workflow, ai-runtime, ai-sandboxes, code-execution; When your project requires running AI-generated code securely and you need an on-demand scalable environment that adjusts automatically based on demand. ### When should I choose eval-view over daytona? Choose eval-view over daytona when Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; Also covers LLM Frameworks; eval-view ships Docker support for self-hosted deployment. ### When should I avoid daytona? Avoid using Daytona if you have strict requirements for the programming languages it supports, since this information is currently unknown. Daytona might not be suitable if your development workflow does not require API access or an online dashboard, as its user interface and API integration are key components. ### When should I avoid eval-view? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is daytona or eval-view more popular on GitHub? daytona has more GitHub stars (72,233 vs 122). Stars measure visibility, not whether either tool fits your constraints. ### Are daytona and eval-view open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to daytona or eval-view? GraphCanon lists graph-backed alternatives at [daytona alternatives](/tools/daytonaio-daytona/alternatives) and [eval-view alternatives](/tools/hidai25-eval-view/alternatives) ([daytona markdown twin](/tools/daytonaio-daytona/alternatives.md), [eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/daytonaio-daytona-vs-hidai25-eval-view.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, daytona or eval-view? daytona: Very active. eval-view: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for daytona and eval-view? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [daytona trust report](/tools/daytonaio-daytona/trust); [eval-view trust report](/tools/hidai25-eval-view/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=daytonaio-daytona`](/api/graphcanon/graph?tool=daytonaio-daytona) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_