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Dagger vs Dgraph

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
Dgraph logo

Dgraph

Databases

Apache 2.0 distributed graph database written in Go, maintained by Hypermode, queried through GraphQL or its own DQL language.

From
Free
Free plan
Yes
Visit DgraphFull review

The short version

  • Free plans on both; paid from $50/mo and $39/mo.
  • Only Dagger lists pipelines as code; only Dgraph lists apache 2.0 licence.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which Dagger and Dgraph actually diverge.

Attributes where Dagger and Dgraph differ
AttributeDaggerDgraph
Pricing modelPer month per team for Dagger CloudFreemium
PlatformsLinux, macOS, Windows, Self-hostedLinux, macOS, Self-hosted, Web
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 Dgraph

  • Apache 2.0 licence
  • Generated GraphQL API
  • DQL query language
  • Predicate sharding
  • Raft replication
  • Distributed ACID transactions
  • Written in Go
  • Full-text and geo indexing

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

Dgraph

  • An application whose core data is a graph, such as permissions, social connections or product relationships, where the frontend already consumes GraphQLnot Dagger
  • A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot Dagger
  • Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot Dagger
  • Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot 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

Dgraph

  • Sharding is by predicate, so a single very hot predicate lives entirely in one Raft group and cannot be split further; adding nodes does not relieve it and the fix is a data model change
  • Stewardship passed from Dgraph Labs to Hypermode after the original company stopped operating independently, so anyone building on it is betting on a second custodian rather than on the original team's roadmap
  • The GraphQL layer is generated and opinionated, so anything it does not express drops you into DQL, which is a second language your team must learn and which no other database speaks
  • The community is a fraction of Neo4j's, so operational answers, tuning experience, hiring and third-party tooling are all thinner, and unusual failure modes in a Zero and Alpha cluster leave you reading source rather than a forum
  • There is no portable graph standard to migrate to; Cypher, Gremlin and SPARQL are all different query models, so the schema and every query is a rewrite if you later leave, and that cost grows with the application

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

Dgraph

Free
  • CommunityFree
    • Native GraphQL
    • Graph queries
    • Full-text search
  • Cloud$39/mo
    • Managed service
    • Auto-scaling
    • Enterprise support

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 Dgraph if

  • You need apache 2.0 licence.
  • You want to start without paying.
  • You work on Linux, macOS, Self-hosted, Web.
  • You also want generated graphql api.
Dgraph review

Questions people ask

Is Dagger or Dgraph better?
Neither clearly leads. Dagger starts at Free and Dgraph at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagger or Dgraph?
Dagger starts at Free and Dgraph at Free.
Does Dagger or Dgraph run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. Dgraph runs on Linux, macOS, Self-hosted, 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 Dgraph is typically brought in for.
What can Dagger do that Dgraph cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding.

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.

Dgraph: Is Dgraph open source?

Yes. The current repository is Apache 2.0, which is a permissive OSI licence, and the project is at v25 under Hypermode's maintenance.

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.

Dgraph: Is it really GraphQL?

It serves a generated GraphQL API, which is real GraphQL for clients. Its native language, DQL, resembles GraphQL syntactically but is Dgraph's own language and is not the GraphQL specification.

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.

Dgraph: How does it compare to Neo4j?

Neo4j has the larger ecosystem, Cypher, and far more operational precedent. Dgraph distributes storage across nodes by default and gives you a GraphQL endpoint without writing resolvers. The choice usually turns on whether you need horizontal scale and a GraphQL surface more than you need ecosystem depth.

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.

Dgraph: What does a production cluster look like?

At minimum a set of Zero nodes for coordination and a replicated set of Alpha nodes for data, typically three of each for fault tolerance, which is a meaningfully larger operational footprint than a single graph server.

Dgraph: Who maintains it now?

Hypermode. Dgraph Labs, the original company, no longer operates it, and that change of custodian is the main non-technical risk to weigh.

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