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Dagger vs Daytona

Dagger logo

Dagger

Developer Tools

Programmable CI/CD engine that runs your pipeline as containers on any runner

From
Free
Rated
-
Full reviewWebsite
Daytona logo

Daytona

Developer Tools

Infrastructure for spinning up secure, sub-second sandboxes to run AI-generated code

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dagger dagger is not a CI provider, so you keep paying for GitHub Actions or GitLab runners underneath it; the Dagger Cloud subscription is an addition to your CI bill, not a replacement for it.; Daytona pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.
  • They diverge on capability: Dagger covers Pipelines as code, Daytona covers Sub-second sandbox creation.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dagger and Daytona actually diverge.

Attributes where Dagger and Daytona differ
AttributeDaggerDaytona
Pricing modelPer month per team for Dagger Cloudusage-based
PlatformsLinux, macOS, Windows, Self-hostedweb, linux, windows, api

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Developer Tools).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Dagger

  • Pipelines as code
  • Local and CI parity
  • Content-addressed caching
  • Dagger Functions and modules
  • CI-provider agnostic
  • Dagger Cloud traces
  • GitHub Checks integration
  • Container-native execution

Only in Daytona

  • Sub-second sandbox creation
  • Per-second billing
  • GPU instances
  • Windows OS support
  • Enterprise BYOC

What people use each for

The jobs each tool is most often brought in to do.

Dagger

  • A platform team maintaining near-identical build YAML across forty repositories that wants one versioned module every repository calls insteadnot Daytona
  • An engineering organisation migrating off a CI provider that does not want to rewrite every pipeline as part of the migrationnot Daytona
  • A team whose engineers waste hours pushing commits to debug CI-only failures and needs to reproduce the exact run locallynot Daytona
  • A monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materiallynot Daytona

Daytona

  • Running AI agent-generated code in a disposable, isolated sandboxnot Dagger
  • Executing untrusted user code for a coding platformnot Dagger
  • Running GPU workloads on demand without provisioning dedicated serversnot Dagger
  • Testing Windows-specific code paths in a sandboxnot Dagger

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Dagger

  • Dagger is not a CI provider, so you keep paying for GitHub Actions or GitLab runners underneath it; the Dagger Cloud subscription is an addition to your CI bill, not a replacement for it.
  • Writing pipelines in Go or TypeScript raises the barrier to entry: a release engineer who could edit a YAML step now needs to read code, and the people who can fix a broken build shrink to those comfortable with the SDK.
  • The engine runs as a container on the runner and needs a persistent cache volume to deliver its main benefit, so ephemeral CI runners give you correctness without the speed, and provisioning durable cache storage is extra platform work.
  • The Team plan caps at ten users and ten million events per month; an organisation of any size crosses that quickly and moves to Enterprise pricing that is not published, so cost at scale is unknowable up front.
  • The module ecosystem is young and thinly maintained relative to the marketplace of a mature CI provider, so integrations that exist as a one-line Action often have to be written yourself as a Dagger function.

Daytona

  • Pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.
  • GPU instances are priced separately and can be significantly more expensive than standard compute for AI-heavy use cases.
  • Enterprise features like SSO, audit logs, and BYOC are only available by contacting sales rather than self-serve.

Pricing, plan by plan

Dagger

Free
  • IndividualFree
    • One user
    • One million events per month
    • Workflow logs and function call traces
  • Team$50/month
    • Up to ten users
    • Ten million events per month
    • Module insights and module catalogue
  • Enterprise$undefined/year
    • Custom user and event limits
    • SSO
    • Managed single-tenant deployment

Daytona

Free
  • Pay-as-you-go$undefined/mo
    • $0.0504 per vCPU/hour
    • $0.0162 per GiB memory/hour
    • $0.000108 per GiB storage/hour after 5 free GiB
  • Startup Program$undefined/mo
    • Up to $50,000 in free credits for qualifying startups
  • Enterprise$undefined/mo
    • Custom usage limits
    • SSO
    • Audit logs

Which should you pick?

Choose Dagger if

  • You need pipelines as code.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Self-hosted.
  • You also want local and ci parity.
Dagger review

Choose Daytona if

  • You need sub-second sandbox creation.
  • You want to start without paying.
  • You work on web, linux, windows, api.
  • You also want per-second billing.
Daytona review

Questions people ask

Is Dagger or Daytona better?
Neither clearly leads. Dagger starts at Free and Daytona at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagger or Daytona?
Dagger starts at Free and Daytona at Free.
Does Dagger or Daytona run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. Daytona runs on web, linux, windows, api.
Can I use Dagger for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dagger best used for?
Dagger is most often used for a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead, an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration, a team whose engineers waste hours pushing commits to debug ci-only failures and needs to reproduce the exact run locally, a monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materially. Of those, a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead and an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration are not what Daytona is typically brought in for.
What can Dagger do that Daytona cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. Daytona covers Sub-second sandbox creation, Per-second billing, GPU instances, Windows OS support.

Answered from the vendors’ own pages

Dagger: Does Dagger replace GitHub Actions?

No. Dagger runs inside GitHub Actions or any other CI. It replaces the YAML that describes your pipeline steps, not the trigger and runner layer.

Daytona: How is Daytona usage metered?

Usage is billed per second across vCPU, memory, and storage consumed, with separate per-hour rates for GPU and Windows instances.

Source
Dagger: Is the engine open source?

Yes, the Dagger engine and SDKs are open source and free. Dagger Cloud, the observability product, is what costs money.

Daytona: Is there a free plan, and what are its limits?

There is no flat free plan, but new signups receive $200 in free compute credit with no credit card required to start.

Source
Dagger: What is an event in the pricing?

Dagger Cloud meters pipeline telemetry events. One million per month is free; the Team plan at 50 USD per month allows ten million.

Daytona: Are discounts available for startups?

Yes, the Startup Program offers up to $50,000 in free credits for qualifying companies.

Source
Dagger: Can I run the same pipeline on my laptop?

Yes, that is the main reason teams adopt it. The dagger CLI executes the identical graph locally, so CI-only failures become reproducible.

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