Softwr

Developer Tools · head to head

Cortex vs Daytona

Cortex logo

Cortex

Developer Tools

Internal developer portal that scores service ownership and maturity rather than just cataloguing services

From
On request
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

  • Only Daytona has a free tier, so it costs nothing to try first.
  • Each has a real cost: Cortex pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.; 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: Cortex covers Service catalogue, 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 Cortex and Daytona actually diverge.

Attributes where Cortex and Daytona differ
AttributeCortexDaytona
Starting priceOn requestFree
Pricing modelquoteusage-based
Free tierNoYes
PlatformsWeb, APIweb, linux, windows, api

Identical on both: 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 Cortex

  • Service catalogue
  • Scorecards
  • Initiatives
  • Self-service templates
  • Query language
  • Eng intelligence
  • Integrations layer
  • On-call and ownership mapping

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.

Cortex

  • A platform team that needs to prove to leadership how far a Kubernetes or framework migration has actually progressed across hundreds of servicesnot Daytona
  • An organisation where ownership of production services is genuinely unknown after reorganisations or acquisitionsnot Daytona
  • Enforcing production readiness standards on new services at creation time rather than at incident reviewnot Daytona
  • Replacing a self-hosted Backstage that is consuming a full-time engineer or two just to stay upgradednot Daytona

Daytona

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

Where each one falls short

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

Cortex

  • Pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.
  • The catalogue is only as accurate as the metadata you supply, so an organisation with inconsistent repository conventions spends its first quarter cleaning data before any scorecard means anything.
  • Scorecards create political friction: publishing a per-team grade turns an engineering standard into a performance metric, and teams will game the rules rather than fix the underlying issue.
  • It is closed source and hosted, so organisations with strict data residency or air-gap requirements have limited options compared with running Backstage themselves.
  • Value scales with organisation size, so a company with fifty engineers and thirty services will find the catalogue tells them nothing they did not already know while still paying an enterprise contract.

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

Cortex

On request
  • Cortex$undefined/year
    • Service catalogue and ownership mapping
    • Scorecards and initiatives
    • Self-service templates

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 Cortex if

  • You need service catalogue.
  • You work on Web, API.
  • You also want scorecards.
Cortex 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 Cortex or Daytona better?
Neither clearly leads. Cortex starts at On request and Daytona at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cortex or Daytona?
Daytona has a free tier; the other does not. Paid plans start at On request for Cortex and Free for Daytona.
Does Cortex or Daytona run on more platforms?
Cortex runs on Web, API. Daytona runs on web, linux, windows, api.
Can I use Daytona for free?
Yes. Daytona has a free tier, so you can try it without paying. Cortex starts at On request.
What is Cortex best used for?
Cortex is most often used for a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services, an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions, enforcing production readiness standards on new services at creation time rather than at incident review, replacing a self-hosted backstage that is consuming a full-time engineer or two just to stay upgraded. Of those, a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services and an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions are not what Daytona is typically brought in for.
What can Cortex do that Daytona cannot?
Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates. Daytona covers Sub-second sandbox creation, Per-second billing, GPU instances, Windows OS support.

Answered from the vendors’ own pages

Cortex: How is Cortex different from Backstage?

Backstage is an open source framework you build and staff. Cortex is a hosted product with scorecards and initiatives out of the box and no platform team required to keep it running.

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
Cortex: Is pricing published?

No. Cortex requires a sales conversation and prepares a custom proposal.

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
Cortex: Can it self-host?

It is offered as a hosted product; on-premise arrangements are handled through sales rather than published.

Daytona: Are discounts available for startups?

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

Source
Cortex: What is the main adoption risk?

Bad or missing service metadata. The catalogue and every scorecard on top of it inherit whatever quality your repositories already have.

Share

Related pages

More on Cortex

More on Daytona

Keep looking

Other head to heads