Apache Airflow vs Meltano
On the evidence we track, Apache Airflow leads this comparison with a composite score of 69/100. 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
LeaderApache Airflow is a workflow orchestration platform that enables users to define data pipelines in Python and schedule their execution across distributed workers. It provides a web interface for visualization and monitoring, plus extensive integrations with cloud platforms and services.
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.
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.
- Databricks
- Snowflake
- dbt Cloud
- Slack
- Salesforce
- PostgreSQL
- MySQL
- MongoDB
- Apache Kafka
- Elasticsearch
- Datadog
- GitHub
- Oracle
- ClickHouse
- Asana
- Zendesk
- Microsoft SQL Server
Apache Airflow
Leader- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
- Tableau
- Redis
- Kubernetes
- Docker
- Apache Spark
- Apache Cassandra
- Apache Flink
- Apache Druid
- Jenkins
- OpenAI
- Anthropic
- Cohere
- Pinecone
- Weaviate
- Qdrant
- Teradata
- SQLite
- Presto
- Trino
- Neo4j
- Airbyte
- +20 more
Meltano
- Singer
- dbt
- Airflow
- Great Expectations
- Dagster
- Superset
- Google Analytics
- BigQuery
- HubSpot
- Jira
- Google Sheets
- Amazon Redshift
- GitLab
- Freshdesk
- Intercom
- AWS S3
- Looker
- Data.world
- Monday.com
- Mailchimp
- LinkedIn Ads
- Airtable
- ActiveCampaign
- Marketo
- +22 more
Apache Airflow 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.