Dagster vs Meltano
On the evidence we track, Dagster leads this comparison with a composite score of 70/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for data engineering tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Dagster
LeaderAn orchestration and observability platform that models data assets, manages their dependencies, and integrates lineage tracking, quality monitoring, and data cataloging for managing pipelines from development to production.
Meltano
Meltano provides teams with an open-source data integration engine that orchestrates extraction, loading, and transformation from multiple sources. It supports various replication methods and includes automatic data quality monitoring, with flexibility to deploy either in a managed cloud environment or as self-hosted infrastructure.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Dagster
LeaderFrom $10/month. Free 30-day trial. Subscription plus metered usage model.
- Solo$10/month + $0.04/credit + $0.01/minute serverless compute
- Core and asset-based orchestration
- Local development (dg CLI)
- Partitions and backfills
- Branch deployments
- Asset checks
- +3 more
- Starter$100/month + $0.035/credit
- All Solo features
- Workflow-based orchestration
- Freshness policies
- Data column lineage
- BI tool integration
- +5 more
- ProContact sales
- All Starter features
- Custom serverless compute
- Cost tracking and insights
- Personalized onboarding support
- Private Slack channel
- +8 more
Meltano
Free open-source version. Managed cloud plans from Starter (200 compute hrs/mo) to Enterprise (unlimited). Pay for compute, not rows.
- Starter-
- 200 compute hours/mo
- Managed infrastructure
- 25 workspaces
- Unlimited users
- 600+ connectors
- +5 more
- Growth-
- 2000 compute hours/mo
- Everything in Starter
- 100 workspaces
- 8 hours of engineering on demand/mo
- Shared account management
- Scale-
- 5000 compute hours/mo
- Everything in Growth
- Unlimited workspaces
- 15 hours of engineering on demand/mo
- Dedicated account management
- +1 more
- EnterpriseContact sales
- Unlimited compute hours/mo
- Everything in Scale
- Custom connectors
- Custom hours of engineering on demand/mo
- Custom SLA
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- dbt
- Snowflake
- Databricks
- Slack
- Datadog
- dbt Cloud
- AWS S3
- Salesforce
- Looker
- Clickhouse
- Airflow
- Singer
Dagster
Leader- Spark
- Azure
- AWS
- Airbyte
- Tableau
- Soda
- Microsoft Teams
- PagerDuty
- Python
- Fivetran
- AWS Redshift
- AWS EMR
- AWS Glue
- AWS Athena
- AWS CloudWatch
- Power BI
- Sigma
- Ray
- lakeFS
- OpenMetadata
- Cube
- SFTP
- Microsoft SharePoint
- Slurm
- +3 more
Meltano
- PostgreSQL
- Great Expectations
- Dagster
- Superset
- Google Analytics
- BigQuery
- HubSpot
- Zendesk
- Jira
- Google Sheets
- Amazon Redshift
- MySQL
- GitHub
- GitLab
- Freshdesk
- Intercom
- Apache Kafka
- Data.world
- Monday.com
- Asana
- Mailchimp
- LinkedIn Ads
- Airtable
- ActiveCampaign
- +27 more
Dagster or Meltano: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.