Daytona vs Eclipse Che
Compare Daytona and Eclipse Che by workflow, pricing, privacy, model support, and best use cases.
Daytona
Choose Daytona when you are building AI agents, code interpreters, or developer platforms that need fast, isolated, stateful code execution. Choose GitHub Codespaces or Gitpod/Ona for full developer workspaces, CodeSandbox for collaborative cloud sandboxes, StackBlitz for browser-native web projects, or E2B when you want a more established AI-agent sandbox category comparison.
Eclipse Che
Eclipse Che is a strong choice for organizations that want open-source, Kubernetes-native, browser-based developer workspaces with enterprise control. It is less suitable for teams that want a fully managed SaaS IDE, built-in AI coding, or a low-operations setup.
Key Differences
Workflow
Daytona is secure sandbox infrastructure for AI agents and code-execution products that need fast, isolated, stateful environments.
Eclipse Che is an open-source Kubernetes-native cloud development environment platform for teams that want centrally managed, browser-based, reproducible developer workspaces.
Pricing
freemium
open-source
Feature Comparison
| Feature | Daytona | Eclipse Che |
|---|---|---|
| Primary workflow | Daytona is secure sandbox infrastructure for AI agents and code-execution products that need fast, isolated, stateful environments. | Eclipse Che is an open-source Kubernetes-native cloud development environment platform for teams that want centrally managed, browser-based, reproducible developer workspaces. |
| Type | resource | framework |
| Editor base | Browser | Browser |
| Pricing model | freemium | open-source |
| Starting price | $0 | $0 |
| Free plan | Yes | Yes |
| Open source | Yes | Yes |
| Local models | No | No |
| BYOK | No | No |
| Platforms | Cloud sandboxes, REST API, SDKs, Docker / OCI images, SSH, Web terminal, VS Code-style access where configured, Linux sandbox environments, Windows sandbox environments, GPU sandbox environments | Browser, Kubernetes, OpenShift, AWS EKS, Azure AKS, Google Kubernetes Engine, Minikube, vCluster, Visual Studio Code - Open Source, JetBrains IDEs, Open VSX |
| Models | Unknown | Unknown |
| Enterprise features | Volume discounts, Custom resource quotas, Custom concurrency limits, Enterprise support, Security review, SDK and API integration support, Custom infrastructure discussions, Sandbox lifecycle management, Snapshot management, GPU sandbox options, Configurable runtime images, Network and firewall configuration options, Organization billing and spending visibility | Kubernetes and OpenShift deployment, OIDC authentication, OpenShift OAuth and Dex integration, Kubernetes RBAC authorization, Multi-user workspace management, Restricted and air-gapped installation support, Standalone Open VSX registry support, CheCluster custom resource configuration, Prometheus and Grafana monitoring integration, Workspace isolation through Kubernetes namespaces and pods |
| Best for | AI agent code execution, Code interpreter infrastructure, Running untrusted AI-generated code, Sandboxed developer tools, Programmatic execution environments, High-concurrency agent workflows, Stateful sandbox sessions, Snapshot-based agent workflows, Products that need isolated code runners, Teams building agent platforms, Secure evaluation of generated code, Infrastructure teams replacing ad hoc Docker execution | Enterprise teams standardizing development environments on Kubernetes or OpenShift, Organizations replacing local workstation setup with centralized browser-based workspaces, Platform engineering teams building cloud development environments, Teams that want devfile-based, version-controlled workspace definitions, Projects that benefit from production-like development runtimes inside Kubernetes pods |
| Not best for | Developers looking for a complete AI code editor, Non-technical users looking for prompt-to-app builders, Teams that only need simple browser-based coding examples, Projects that require a GitHub-native CDE workflow, Users who want fixed monthly pricing with no usage-based compute, Small frontend demos better served by StackBlitz or CodeSandbox, Teams unwilling to design sandbox security, secrets, and network policies | Small teams that want a simple managed IDE with no Kubernetes operations, Developers looking for an AI coding assistant or prompt-to-app builder, Teams that do not use containers, Kubernetes, OpenShift, or devfile workflows, Organizations without capacity to manage storage, networking, OIDC, RBAC, upgrades, and cluster sizing, Solo developers who mainly need lightweight local development |
Use Case Winners
Eclipse Che is built around a Browser editor workflow.
Both Daytona and Eclipse Che have comparable signals here.
Daytona lists more team or enterprise controls.
Daytona has stronger frontend or web workflow signals.
Neither tool shows a strong signal for this use case in the current structured data.
Both Daytona and Eclipse Che have comparable signals here.
Pricing Comparison
Daytona
- Free Trial$0
$200 in free compute included for trying Daytona sandboxes; no credit card required on the public pricing page.
- Pay-as-you-go Compute$0.000014 / vCPU-second
Usage-based CPU sandbox pricing, equivalent to about $0.0504 per vCPU-hour.
- Memory$0.00000450 / GiB-second
Usage-based memory pricing, equivalent to about $0.0162 per GiB-hour.
- Storage$0.00000003 / GiB-second
5 GB free, then usage-based storage pricing after the free allowance.
- GPUUsage-based / second
GPU sandbox pricing is listed for options such as Nvidia H100 and RTX PRO 6000, billed per second.
Eclipse Che
- Open Source$0 / month
Eclipse Che is free and open source under the Eclipse Public License 2.0.
- Self-Hosted InfrastructureUsage-based
You provide and pay for Kubernetes, OpenShift, storage, networking, identity, and compute resources.
- Hosted Trial / Samples$0
Public sample workspaces may be available through Red Hat-hosted OpenShift workspaces, subject to availability and account requirements.
Privacy & Security
Daytona
Daytona sandboxes may run code, files, dependencies, generated outputs, terminal logs, environment variables, snapshots, and API-controlled workflows. Because the platform is commonly used to execute AI-generated or untrusted code, teams should strictly control secrets, network access, filesystem persistence, snapshot retention, image provenance, outbound calls, and sandbox lifetime before connecting Daytona to production systems or sensitive data.
Eclipse Che
Eclipse Che is typically self-hosted on infrastructure controlled by the organization. Source code, workspace containers, credentials, logs, and runtime data are governed by the chosen Kubernetes or OpenShift cluster, storage backend, identity provider, RBAC policies, and extension registry configuration. Teams should review cluster access, namespace isolation, secrets handling, image provenance, Open VSX registry policy, and log retention before rollout.
Choose Daytona if...
- AI agent code execution
- Code interpreter infrastructure
- Running untrusted AI-generated code
- Sandboxed developer tools
- Programmatic execution environments
Choose Eclipse Che if...
- Enterprise teams standardizing development environments on Kubernetes or OpenShift
- Organizations replacing local workstation setup with centralized browser-based workspaces
- Platform engineering teams building cloud development environments
- Teams that want devfile-based, version-controlled workspace definitions
- Projects that benefit from production-like development runtimes inside Kubernetes pods
Avoid Daytona if...
- Developers looking for a complete AI code editor
- Non-technical users looking for prompt-to-app builders
- Teams that only need simple browser-based coding examples
- Projects that require a GitHub-native CDE workflow
- Users who want fixed monthly pricing with no usage-based compute
Avoid Eclipse Che if...
- Small teams that want a simple managed IDE with no Kubernetes operations
- Developers looking for an AI coding assistant or prompt-to-app builder
- Teams that do not use containers, Kubernetes, OpenShift, or devfile workflows
- Organizations without capacity to manage storage, networking, OIDC, RBAC, upgrades, and cluster sizing
- Solo developers who mainly need lightweight local development