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Dagger vs Google Cloud SQL

Dagger logo

Dagger

Developer Tools

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

From
Free
Free plan
Yes
Visit DaggerFull review
Google Cloud SQL logo

Google Cloud SQL

Databases

Fully managed relational database service for MySQL, PostgreSQL, and SQL Server

From
Free
Free plan
Yes
Visit Google Cloud SQLFull review

The short version

  • Free plans on both; paid from $50/mo and $25/mo.
  • Only Dagger lists pipelines as code; only Google Cloud SQL lists high Availability.
  • Where Google Cloud SQL falls short: locked into Google Cloud ecosystem with limited cross-cloud portability.
  • Prices and features on this page were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dagger and Google Cloud SQL actually diverge.

Attributes where Dagger and Google Cloud SQL differ
AttributeDaggerGoogle Cloud SQL
Pricing modelPer month per team for Dagger CloudUsage-based
PlatformsLinux, macOS, Windows, Self-hostedWeb
CategoryDeveloper ToolsDatabases

Identical on both: starting price (Free), free tier (Yes).

Not yet recorded: founded for Dagger.

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 Google Cloud SQL

  • High Availability
  • Automated Backups
  • Point-in-time Recovery
  • Encryption
  • Regional/Zonal Instances
  • Read Replicas
  • Private IP
  • BigQuery

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

Google Cloud SQL

  • Transaction processingnot Dagger
  • Data storagenot Dagger
  • Application backendnot Dagger
  • Reportingnot Dagger
  • Data analyticsnot 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

Google Cloud SQL

  • Locked into Google Cloud ecosystem with limited cross-cloud portability
  • Pay-as-you-go pricing can become expensive with unpredictable workloads
  • Limited customization options compared to self-managed databases

Pricing, plan by plan

Dagger

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

Google Cloud SQL

Free
  • Free TierFree
    • db-f1-micro instance
    • 30GB storage
    • Limited usage
  • Standard$25/mo
    • High availability
    • Automated backups
    • Point-in-time recovery

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 Google Cloud SQL if

  • You need high availability.
  • You want to start without paying.
  • You also want automated backups.
Google Cloud SQL review

Questions people ask

Is Dagger or Google Cloud SQL better?
Neither clearly leads. Dagger starts at Free and Google Cloud SQL at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagger or Google Cloud SQL?
Dagger starts at Free and Google Cloud SQL at Free.
Does Dagger or Google Cloud SQL run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. Google Cloud SQL runs on Web.
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 Google Cloud SQL is typically brought in for.
What can Dagger do that Google Cloud SQL cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption.

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.

Google Cloud SQL: What database engines does Google Cloud SQL support?

Google Cloud SQL supports MySQL, PostgreSQL, and SQL Server. Users can choose their preferred engine when provisioning an instance and Google handles automated backups, replication, patching, and scaling.

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.

Google Cloud SQL: Does Google Cloud SQL have a free tier?

Google Cloud SQL does not have a free tier, though new users receive free trial credits from Google Cloud Platform. Pricing is based on compute resources (CPU and memory) and storage used, with options for committed use discounts.

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.

Google Cloud SQL: Can Google Cloud SQL scale automatically?

Yes. Cloud SQL automatically scales database storage and compute resources to handle increased workloads without manual intervention, and includes automated backups and high availability configurations.

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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