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Developer Tools · head to head

Daytona vs Steampipe

Daytona logo

Daytona

Developer Tools

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

From
Free
Rated
-
Steampipe logo

Steampipe

Developer Tools

Query cloud APIs, SaaS tools and code with SQL, with no extract or load step

From
Free
Rated
-

The short version

  • Each has a real cost: Daytona pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.; Steampipe aGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • They diverge on capability: Daytona covers Sub-second sandbox creation, Steampipe covers SQL over live APIs.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Daytona and Steampipe actually diverge.

Attributes where Daytona and Steampipe differ
AttributeDaytonaSteampipe
Pricing modelusage-basedOpen source, with paid hosting through Turbot Pipes
Platformsweb, linux, windows, apimacOS, Linux, Windows, Docker, Web

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 Daytona

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

Only in Steampipe

  • SQL over live APIs
  • Wide plugin set
  • Embedded Postgres
  • Compliance benchmarks
  • Joins across providers
  • Hosted option

What people use each for

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

Daytona

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

Steampipe

  • Security teams answering posture questions against live cloud accounts rather than a nightly exportnot Daytona
  • Compliance evidence gathering where the answer must reflect the account at the moment it is askednot Daytona
  • Inventory and drift questions spanning several cloud providers in one querynot Daytona
  • Engineers who would rather write SQL than learn each provider command line toolnot Daytona

Where each one falls short

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

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.

Steampipe

  • AGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • Dashboards, benchmarks and mods were removed from Steampipe entirely at version 1.0 in October 2024 and now live in a separate product, so pre-2024 documentation and tutorials describe commands that no longer exist.
  • Live querying is bound by cloud provider API rate limits and keeps no persistent store by default, which is why a separate DuckDB-backed product exists for log volumes and why large accounts return slowly.
  • The company is fifteen people and bootstrapped, maintaining four command line tools plus a hosted service plus two further products, and the newer tools have thin community traction relative to that surface area.
  • Hosted tiers include only three users regardless of tier, with additional Enterprise users charged separately, so a team of thirty costs an order of magnitude more than the headline figure before compute and storage are counted.

Pricing, plan by plan

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

Steampipe

Free
  • Steampipe CLIFree
    • AGPL-3.0
    • All plugins
    • No user or query limits
  • Pipes DeveloperFree
    • One user
    • 400 compute minutes
    • 3GB storage
  • Pipes Team$49/month
    • Three users
    • 2,000 compute minutes
    • 20GB storage
  • Pipes Enterprise$249/month
    • Three users
    • 10,000 compute minutes
    • 100GB storage

Which should you pick?

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.

Choose Steampipe if

  • You need sql over live apis.
  • You want to start without paying.
  • You work on macOS, Linux, Windows, Docker, Web.
  • You also want wide plugin set.

Questions people ask

Is Daytona or Steampipe better?
Neither clearly leads. Daytona starts at Free and Steampipe at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Daytona or Steampipe?
Daytona starts at Free and Steampipe at Free.
Does Daytona or Steampipe run on more platforms?
Daytona runs on web, linux, windows, api. Steampipe runs on macOS, Linux, Windows, Docker, Web.
Can I use Daytona for free?
Both have a free tier, so you can try either at no cost before committing.
What is Daytona best used for?
Daytona is most often used for running ai agent-generated code in a disposable, isolated sandbox, executing untrusted user code for a coding platform, running gpu workloads on demand without provisioning dedicated servers, testing windows-specific code paths in a sandbox. Of those, running ai agent-generated code in a disposable, isolated sandbox and executing untrusted user code for a coding platform are not what Steampipe is typically brought in for.
What can Daytona do that Steampipe cannot?
Daytona covers Sub-second sandbox creation, Per-second billing, GPU instances, Windows OS support. Steampipe covers SQL over live APIs, Wide plugin set, Embedded Postgres, Compliance benchmarks.

Answered from the vendors’ own pages

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
Steampipe: When did Steampipe become AGPL?

May 2021, about four months after the project went public. It is a settled licence rather than a recent change, and predates the Business Source Licence wave it is often confused with.

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
Steampipe: Where did the dashboards and benchmarks go?

Into Powerpipe. They were deprecated in March 2024 and removed from Steampipe at version 1.0 in October 2024, so the check, dashboard, mod and variable commands are gone.

Daytona: Are discounts available for startups?

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

Source
Steampipe: Is it fast on a large cloud estate?

Not always. Queries call provider APIs at request time, so rate limits rather than query planning set the pace, and there is no persistent store by default.

Steampipe: Does the AGPL affect internal use?

Running it internally for your own analysis is fine. Putting a web interface in front of it that other people use is where the network clause becomes a question for your legal team.

Steampipe: Is a bootstrapped vendor a risk?

It cuts both ways. There is no investor pressure toward a licence change or an exit, and there are also fifteen people supporting a large product surface.

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