Apache Airflow vs Meltano
On the evidence we track, Apache Airflow leads this comparison with a composite score of 73/100. 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.
Apache Airflow
LeaderA community-built orchestration system that enables users to define data pipelines and tasks in Python, execute them on distributed workers, and monitor progress through a web-based interface. It supports dynamic pipeline generation, extensive third-party integrations, and operates best for batch-oriented workflows.
Meltano
Meltano provides a code-first approach to data integration, offering 600+ pre-built connectors with compute-time pricing and integrated governance. It enables teams to combine data extraction, loading, and transformation workflows with native dbt support and orchestration capabilities.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Apache Airflow
LeaderFree, open-source project. Managed cloud versions available through third parties.
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.
- Snowflake
- PostgreSQL
Apache Airflow
Leader- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
- Databricks
- dbt Cloud
- Slack
- Salesforce
- Tableau
- MySQL
- MongoDB
- Redis
- Kubernetes
- Docker
- Apache Spark
- Apache Kafka
- Apache Cassandra
- Apache Flink
- Apache Druid
- Elasticsearch
- Datadog
- Jenkins
- GitHub
- OpenAI
- Anthropic
- +24 more
Meltano
- Singer
- dbt
- Airflow
- Great Expectations
- Dagster
- Superset
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.