Comparison

Everstack vs Daytona

Daytona builds a fast, well-designed sandbox runtime, and the company is still developing it. But the open source repository behind its 71,871 stars stopped receiving updates in June 2026, when core development moved to a private codebase. If your plan was to self-host it, that is the fact that decides this.

EverstackEverstack
vs
DaytonaDaytona
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What is Daytona?

Daytona is a secure and elastic infrastructure runtime for AI-generated code, built on OCI and Docker compatibility. Its README describes sandboxes with a dedicated kernel, filesystem, network stack and allocated resources, while its documentation describes default sandboxes as Linux containers with VM sandboxes as a separate option. It documents sub-90ms starts and stateful snapshots. Its public repository has 71,871 GitHub stars, a maintenance notice stating that core development moved to a private codebase in June 2026, and no LICENSE file since 23 June 2026.

Why teams choose Everstack

  • An open source repository that is still receiving updates
  • Self-hosting is the supported path, not a fork of an archived tree
  • The sandbox arrives with the gateway, agent runtime and evaluations around it

Daytona: Strengths & Limitations

Strengths

  • They gave a defensible reason for closing the source. Daytona's announcement argues that publishing an isolation layer, kernel boundaries and orchestration logic hands the blueprint of that boundary to anyone who wants to probe it with an AI. For a sandbox vendor that is a serious argument, not a pretext.
  • Enormous reach: 71,871 GitHub stars, one of the highest counts in developer infrastructure.
  • A genuinely fast runtime. Daytona documents sandboxes starting in under 90 milliseconds from code to execution, which is excellent.
  • Their README describes full composable computers with a dedicated kernel, filesystem, network stack and allocated vCPU, RAM and disk, built on OCI and Docker compatibility.
  • Stateful environment snapshots for persistent agent operations across sessions, which is a real differentiator for long-running agents.
  • A polished hosted product with SDKs, an API and a CLI, and the company is actively developing it.

Limitations

  • The open source repository is no longer maintained. Its README states: 'As of June 2026, Daytona's core development has moved to a private codebase. This repository will receive no further updates, fixes, or releases.'
  • The last commit to daytonaio/daytona landed on 25 June 2026. The 71,871 stars are attached to a tree that has stopped moving.
  • The repository is explicitly offered 'as is and without support or warranty', and the licence link points at the v0.190.0 tag rather than the default branch.
  • If you self-host it today you are running an unmaintained snapshot, including for security fixes.
  • The licence went from Apache-2.0 to AGPL-3.0 to gone. The initial commit on 6 February 2024 was Apache-2.0; a commit on 28 April 2025 relicensed the project to AGPL-3.0 alongside the AI-sandbox pivot, shipped as v0.100.0; and a commit on 23 June 2026 deleted the LICENSE file entirely. GitHub now reports the repository licence as none. The last open release, v0.190.0, is AGPL-3.0, and the README points forks at that tag.
  • The isolation story is contested by Daytona's own materials. Their documentation says default sandboxes are Linux containers, with VM sandboxes as a separate option, while the README claims each sandbox has a dedicated kernel, filesystem and network stack. We report both rather than picking one.

Everstack advantage

A repository that still gets security fixesFirecracker, Docker and Kubernetes backendsSandbox traces join model and agent tracesOne Apache-2.0 licence across the platform

The facts, side by side

Licence, deployment model and list price, taken from each vendor's own documentation. Every source is linked at the bottom of this page.

FactEverstackDaytona
Open source statusApache-2.0, actively developed.The public repository is no longer maintained. Its README states core development moved to a private codebase as of June 2026 and that the repository will receive no further updates, fixes or releases.
Last commit to the public repositoryOngoing.25 June 2026, a maintenance notice and a licence link fix.
Security fixes for self-hostersShipped in the same repository you run.None expected. The repository is offered as is and without support or warranty.
Licence historyApache-2.0 from the first commit, unchanged.Apache-2.0 at the initial commit on 6 February 2024, relicensed to AGPL-3.0 on 28 April 2025 with the AI-sandbox pivot and shipped as v0.100.0, then the LICENSE file was deleted on 23 June 2026. GitHub now reports the repository licence as none. The last open release, v0.190.0, is AGPL-3.0, and the README points forks at that tag.
Isolation primitive (resolved)Firecracker microVM, plus Docker and Kubernetes backends.Contested by their own materials. Daytona's documentation describes default sandboxes as Linux containers, with VM sandboxes as a separate option, while the README claims each sandbox has a dedicated kernel, filesystem and network stack. Both statements are theirs, and we are not harmonising them.
GitHub starsFar fewer.71,871 as of 31 August 2026, attached to a tree that stopped moving in June.
Sandbox start timeDepends on backend and warm pool configuration. We do not publish a single headline number.Daytona documents sandboxes spinning up in under 90 milliseconds, which is genuinely fast.
SnapshotsSnapshot support exists but is less mature than Daytona's; we would not claim parity here.Stateful environment snapshots for persistent agent operations across sessions, and a well-developed part of the product.
Bring Your Own ComputeNot applicable. The whole platform runs on your infrastructure, control plane included.A real and supported middle path: sandbox workloads run on your own runner nodes with official Helm charts, while Daytona's hosted control plane, dashboard and database stay with Daytona. Good if your constraint is where code executes, insufficient if it is that no vendor sits in the path.
Gateway, agent runtime and evaluationsSame control plane, sharing one trace.Out of scope. Daytona is the execution runtime.
Hosted productEverstack Cloud, or self-host.Actively developed and available. The company continues to build; it is the public repository that stopped.

Repository status, README text, commit history and star count read from daytonaio/daytona and the GitHub API on 31 August 2026. Licence history read from the commit log: Apache-2.0 at the initial commit, AGPL-3.0 from commit 5271af9f, and the LICENSE file deleted in commit b40f732a. Product claims are from Daytona's own documentation, which is where the isolation description conflicts with the README. Daytona's hosted product is not affected by the repository notice.

Feature comparison

Direct capability comparison across key dimensions

FeatureEverstackDaytona
Sandbox
MicroVM-class isolationContested, see facts
OCI and Docker compatible images
Stateful snapshotsLess mature
Sub-100ms cold start
Kubernetes backend
Deployment
Maintained open source you can self-host
Security fixes for self-hosters
Platform
Multi-provider model gateway
Stateful agent runtime
Evaluations and scoring
Traces spanning sandbox and model calls
Ecosystem
GitHub reach

The same job, in both products

Working code rather than adjectives. Each snippet follows the quickstart published by the product it belongs to.

Create a sandbox and run code

The API shapes are close, which is what you would expect from two products solving the same problem. The decision here is not ergonomics.

Everstack

sandbox.ts
import Everstack from "@everstack/node";const client = new Everstack({ apiKey: process.env.EVERSTACK_API_KEY });const sandbox = await client.sandboxes.create({ template: "python" });const result = await sandbox.exec("python -c 'print(2 + 2)'");console.log(result.stdout);await sandbox.stop();

Daytona

sandbox.py
from daytona import Daytonadaytona = Daytona()sandbox = daytona.create()response = sandbox.process.code_run("print(2 + 2)")print(response.result)sandbox.delete()

Key evaluation questions

What to ask when comparing Daytona to Everstack

QuestionEverstackDaytona
Is the open source version still getting updates?Yes, including security fixes.No. The README states no further updates, fixes or releases as of June 2026.
What licence does the public repository carry?Apache-2.0, unchanged since the first commit.None that GitHub can detect. The LICENSE file was deleted in June 2026; the last open release, v0.190.0, is AGPL-3.0.
How fast does a sandbox start?Depends on backend and warm pool. No single published number.Under 90 milliseconds, which is faster than we claim.
Are stateful snapshots production ready?Supported, but less mature than Daytona's.Yes, and a well-developed part of the product.
Does the sandbox come with a model gateway?Yes, sharing one trace.No, that is a separate system.

Feature-by-feature analysis

Where each product is genuinely stronger, row by row

Whether the open source you self-host is maintained

Everstack wins
Everstack

Apache-2.0 and actively developed, including security fixes, in the repository you run.

Daytona

The public repository states plainly that core development moved to a private codebase in June 2026 and that it will receive no further updates, fixes or releases.

Why Everstack

For anyone whose reason to self-host is control or compliance, running an unmaintained tree is the opposite of what they were buying. Daytona is being honest about it, which is more than some projects manage.

Raw start latency

Daytona wins
Everstack

Depends on backend and warm pool configuration, and we do not publish a single headline number.

Daytona

Under 90 milliseconds from code to execution, documented by Daytona.

Why Daytona

This is a real advantage and it is theirs. If you spawn a sandbox per request rather than per session, it may be the only number that matters.

What surrounds the sandbox

Everstack wins
Everstack

The model gateway that produced the code, the agent that orchestrated it, the memory it read and the evaluation that scored it are all on the same control plane and in the same trace.

Daytona

The execution runtime. Everything around it is a system you choose and integrate.

Why Everstack

Debugging an agent that wrote bad code means seeing the prompt, the completion and the execution together.

Moving from Daytona to Everstack

If you are running the open source Daytona build, the pressing question is not feature parity but maintenance: you are on a tree that stopped receiving fixes in June 2026. If you are on Daytona's hosted product, none of that applies and this is an ordinary comparison.

  1. 1

    Establish which Daytona you are actually on

    The hosted product is actively developed. The public repository is not. These are very different positions and the rest of the plan depends on which one you are in.

  2. 2

    Map the lifecycle calls

    daytona.create maps to sandboxes.create, process.code_run to exec, and delete to stop. Filesystem operations have direct equivalents.

  3. 3

    Rebuild images as templates

    Both are OCI-derived, so a Dockerfile usually carries over with minimal edits.

  4. 4

    Re-plan anything built on snapshots

    Daytona's stateful snapshots are more mature than ours. If your agent architecture depends on them, test that path carefully before committing to a move.

What breaks

  • The Daytona SDK surface has no line-for-line Everstack equivalent and needs rewriting.
  • Workflows built on Daytona's snapshot semantics need re-designing, since our snapshot support is less mature.
  • Daytona CLI usage in scripts and CI has to be replaced.

What does not carry over

  • Existing snapshots and their state.
  • Sandbox execution history.
  • Daytona-specific image registry entries.

Read this part first

When to choose Daytona instead

Daytona builds a genuinely good runtime and the company is still developing it. Pick Daytona over Everstack when any of these is true.

  • You want their hosted product. The repository notice concerns the open source tree, not the commercial service, and the service is actively developed.
  • Cold start is your binding constraint. Under 90 milliseconds from code to execution is faster than we claim, and if you are spawning sandboxes per request that matters more than anything else on this page.
  • Stateful snapshots are central to your agent architecture. Daytona's snapshot support is more mature than ours and we are not going to pretend otherwise.
  • Execution is the whole problem and you already have a gateway, agent runtime and observability you are happy with.
  • You want the option with the largest community footprint, with the caveat that the repository behind those stars has stopped moving.

Frequently asked questions

Common questions about choosing between Everstack and Daytona

Ready to get started?

See how Everstack compares to Daytona for your specific use case.

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Sources & References

daytonaio/daytona repositoryDaytona maintenance notice (README)Daytona documentationEverstack licence (Apache-2.0)

Last reviewed: August 31, 2026. This comparison is for informational purposes and reflects our understanding of competitor capabilities based on publicly available documentation.

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