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Developer Tools · head to head

Dagger vs Thought Machine

Dagger logo

Dagger

Developer Tools

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

From
Free
Free plan
Yes
Full reviewWebsite
Thought Machine logo

Thought Machine

Technology

Cloud native core banking where products are written as smart contracts

From
On request
Free plan
No
Full reviewWebsite

The short version

  • Only Dagger has a free tier, so it costs nothing to try first.
  • 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.; Thought Machine a core replacement is a two to four year programme at an established bank, and the licence is a minority of total cost against system integrator fees, parallel running and data migration.
  • They diverge on capability: Dagger covers Pipelines as code, Thought Machine covers Smart contract product engine.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Dagger and Thought Machine actually diverge.

Attributes where Dagger and Thought Machine differ
AttributeDaggerThought Machine
Starting priceFreeOn request
Pricing modelPer month per team for Dagger Cloudquote
Free tierYesNo
PlatformsLinux, macOS, Windows, Self-hostedWeb, API, Cloud
CategoryDeveloper ToolsTechnology

Identical on both: user rating (Not yet rated).

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 Thought Machine

  • Smart contract product engine
  • Cloud native architecture
  • Real time ledger
  • Vault Payments
  • API first design
  • Multi entity and multi currency
  • Product versioning and testing
  • Configurable posting rules

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 Thought Machine
  • An engineering organisation migrating off a CI provider that does not want to rewrite every pipeline as part of the migrationnot Thought Machine
  • A team whose engineers waste hours pushing commits to debug CI-only failures and needs to reproduce the exact run locallynot Thought Machine
  • A monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materiallynot Thought Machine

Thought Machine

  • A large bank launching a separate digital brand on a clean core rather than migrating the back booknot Dagger
  • A bank whose product launches are blocked by vendor change requests on a legacy corenot Dagger
  • An institution needing real time balances and postings for instant payment obligationsnot Dagger
  • A group consolidating multiple country cores onto one multi entity platformnot 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.

Thought Machine

  • A core replacement is a two to four year programme at an established bank, and the licence is a minority of total cost against system integrator fees, parallel running and data migration.
  • The smart contract model presumes a bank can write and maintain Python financial products, and institutions without that engineering capability end up outsourcing the very flexibility they bought.
  • Cloud infrastructure cost sits with the bank and is not trivial at scale, so total cost of ownership comparisons against a hosted legacy core often miss a large recurring line.
  • Thought Machine has made two rounds of job cuts pursuing profitability, which is a legitimate supplier stability concern for a system a bank expects to run for fifteen years.
  • The functional footprint is core ledger and product engine, so origination, collections, regulatory reporting and channels all come from other vendors, and the integration estate around Vault is the bank's problem to design and own.

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

Thought Machine

On request
  • Vault Core$undefined/year
    • Quoted per institution, typically on account volumes or annual contract value
    • Implementation and system integrator costs commonly exceed the licence fee
    • Cloud infrastructure costs are the bank's and are not included

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 Thought Machine if

  • You need smart contract product engine.
  • You work on Web, API, Cloud.
  • You also want cloud native architecture.
Thought Machine review

Questions people ask

Is Dagger or Thought Machine better?
Neither clearly leads. Dagger starts at Free and Thought Machine at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagger or Thought Machine?
Dagger has a free tier; the other does not. Paid plans start at Free for Dagger and On request for Thought Machine.
Does Dagger or Thought Machine run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. Thought Machine runs on Web, API, Cloud.
Can I use Dagger for free?
Yes. Dagger has a free tier, so you can try it without paying. Thought Machine starts at On request.
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 Thought Machine is typically brought in for.
What can Dagger do that Thought Machine cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. Thought Machine covers Smart contract product engine, Cloud native architecture, Real time ledger, Vault Payments.

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.

Thought Machine: Is Vault Core genuinely cloud native?

Yes. It is containerised, runs on Kubernetes on public cloud, and posts in real time rather than in overnight batch.

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.

Thought Machine: How long does a migration take?

Eighteen months at the absolute fastest for a narrow greenfield launch; two to four years for a phased migration at an established bank.

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.

Thought Machine: Does the licence fee represent the total cost?

No. Implementation, system integration, parallel running and cloud infrastructure typically cost more than the licence over the programme.

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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