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Automation Integration · head to head

Dagster vs Meltano

Dagster logo

Dagster

Automation Integration

Data orchestration platform with asset lineage and AI-native observability

From
Free
Rated
-
Full reviewWebsite
Meltano logo

Meltano

Automation Integration

Open source ELT built on the Singer tap and target ecosystem, configured as code

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dagster learning curve steeper than simpler task schedulers; Meltano the company behind Meltano wound down in December 2025 and the project was transferred to Matatika, a much smaller organisation, so roadmap velocity and the size of the maintenance team are now materially lower than the tool's reputation suggests.
  • They diverge on capability: Dagster covers Asset-centric orchestration, Meltano covers Singer plugin management.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dagster and Meltano actually diverge.

Attributes where Dagster and Meltano differ
AttributeDagsterMeltano
Pricing modelFree open-source core plus paid cloud platformOpen source, no licence fee
PlatformsCloud, Self-hostedLinux, macOS, Docker, Windows (via WSL)

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Automation Integration).

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 Dagster

  • Asset-centric orchestration
  • Lineage tracking
  • Data quality monitoring
  • Multi-tool integration
  • Branch deployments
  • Dagster+ AI
  • Hybrid deployment

Only in Meltano

  • Singer plugin management
  • Project as code
  • Environments
  • Incremental state
  • dbt integration
  • Custom taps
  • Orchestrator hooks
  • Container deployment

What people use each for

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

Dagster

  • Orchestrating multi-stage data transformation pipelinesnot Meltano
  • Tracking data lineage across transformation toolsnot Meltano
  • Monitoring data quality and asset healthnot Meltano
  • Coordinating dbt and Snowflake workflowsnot Meltano

Meltano

  • A data team that wants to stop paying per-row connector fees on high-volume sources they can extract themselvesnot Dagster
  • Loading from an API that no commercial ELT vendor supports, by writing a tap with the Meltano SDKnot Dagster
  • Keeping pipeline configuration in the same Git repository and review process as the rest of the platform codenot Dagster
  • A regulated environment where extraction must run inside your own network with no data passing through a vendornot Dagster

Where each one falls short

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

Dagster

  • Learning curve steeper than simpler task schedulers
  • Asset-centric model requires redesigning existing task-based pipelines
  • Pricing complex with per-credit costs on top of base fee
  • Open-source version requires self-hosting infrastructure
  • Limited to data workflows; not suitable for general automation

Meltano

  • The company behind Meltano wound down in December 2025 and the project was transferred to Matatika, a much smaller organisation, so roadmap velocity and the size of the maintenance team are now materially lower than the tool's reputation suggests.
  • Singer connector quality varies enormously; a tap may be maintained, abandoned, or maintained only for the subset of endpoints its original author needed, and you will not know which until a schema change breaks a load at 3am.
  • There is no managed hosting from the project itself, so someone on your team owns scheduling, secrets, retries, alerting and upgrades, which is real headcount that a per-row SaaS bill was buying for you.
  • It is command-line and YAML first with no meaningful web interface, so analysts who are not comfortable in Git and a terminal cannot maintain pipelines themselves.
  • Debugging spans three layers, the tap, Meltano itself and the target, and each has its own logging conventions, so failures often require reading Python source in a third-party connector.

Pricing, plan by plan

Dagster

Free
  • Open SourceFree
    • Self-hosted deployment
    • Full orchestration engine
    • Community support
  • Solo$10/month
    • 1 user and 1 code location
    • Pay-as-you-go credits at $0.040 per credit
    • 1 deployment
  • Starter$100/month
    • Up to 3 users and 5 code locations
    • Better credit rate at $0.035 per credit
    • 1 deployment
  • Pro$null/custom
    • Unlimited code locations and deployments
    • Custom serverless compute pricing
    • Personalized onboarding

Meltano

Free
  • MeltanoFree
    • MIT licensed, self-hosted
    • No paid Meltano Cloud tier; it was retired before the company wound down
    • Community support via Slack and GitHub

Which should you pick?

Choose Dagster if

  • You need asset-centric orchestration.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want lineage tracking.
Dagster review

Choose Meltano if

  • You need singer plugin management.
  • You want to start without paying.
  • You work on Linux, macOS, Docker, Windows (via WSL).
  • You also want project as code.
Meltano review

Questions people ask

Is Dagster or Meltano better?
Neither clearly leads. Dagster starts at Free and Meltano at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagster or Meltano?
Dagster starts at Free and Meltano at Free.
Does Dagster or Meltano run on more platforms?
Dagster runs on Cloud, Self-hosted. Meltano runs on Linux, macOS, Docker, Windows (via WSL).
Can I use Dagster for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dagster best used for?
Dagster is most often used for orchestrating multi-stage data transformation pipelines, tracking data lineage across transformation tools, monitoring data quality and asset health, coordinating dbt and snowflake workflows. Of those, orchestrating multi-stage data transformation pipelines and tracking data lineage across transformation tools are not what Meltano is typically brought in for.
What can Dagster do that Meltano cannot?
Dagster covers Asset-centric orchestration, Lineage tracking, Data quality monitoring, Multi-tool integration. Meltano covers Singer plugin management, Project as code, Environments, Incremental state.

Answered from the vendors’ own pages

Dagster: What does Solo plan at $10/month include?

Solo includes 1 user, 1 code location, 1 deployment, and serverless compute at $0.010/minute, with 30-day free trial.

Source
Meltano: Is Meltano still maintained after the company shut down?

Yes. Arch, formerly Meltano, was acquired by Matatika in December 2025 and the open source project continues under their stewardship, with releases through 2026.

Dagster: How are credits calculated on Dagster+?

Each asset materialization and ops execution costs 1 credit. Solo plan charges $0.040 per credit; Starter reduces to $0.035 per credit.

Source
Meltano: Is there a hosted Meltano?

Not from the project. Meltano Cloud was retired, and hosting now comes from Matatika or from running the container yourself.

Dagster: Is Dagster open-source available for free?

Yes, Dagster open-source is free and includes the full orchestration engine for self-hosted deployment with community support.

Source
Meltano: How does it compare on cost with Fivetran?

Meltano has no licence fee, so the comparison is your engineering time versus Fivetran's per-monthly-active-row billing. High-volume, low-complexity sources favour Meltano; long tails of fiddly SaaS APIs favour Fivetran.

Meltano: Can I use Airbyte connectors with it?

Yes, Meltano can run Airbyte source connectors through a bridge, which widens the connector pool beyond Singer taps.

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