Apache Airflow vs Kestra
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.
Kestra
An open-source platform designed for orchestrating complex, long-running workflows across data pipelines, AI systems, and infrastructure operations. Supports multiple languages and deployment models (cloud, self-hosted, air-gapped), with built-in reliability features like retries, backfills, and comprehensive observability.
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.
Kestra
Free open-source tier; managed and self-hosted enterprise options available
- Open SourceFree
- Workflow design & execution
- Scheduling & event triggers
- Real-time processing
- Embedded code editor
- Git integration & versioning
- +1 more
- Kestra CloudManaged cloud orchestration
- Fully managed hosting
- Built-in security and governance
- Role-based access control
- Audit logs
- Asset lineage
- +2 more
- EnterpriseContact sales
- Annual subscription model
- Customer success program with SLA
- 24-hour response time
- Audit logs and governance
- Multi-tenancy support
- +2 more
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.
- Slack
- Salesforce
- PostgreSQL
- Kubernetes
- Docker
- Apache Spark
- Apache Kafka
- GitHub
- OpenAI
- Anthropic
- Airbyte
- PagerDuty
Apache Airflow
Leader- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
- Databricks
- Snowflake
- dbt Cloud
- Tableau
- MySQL
- MongoDB
- Redis
- Apache Cassandra
- Apache Flink
- Apache Druid
- Elasticsearch
- Datadog
- Jenkins
- Cohere
- Pinecone
- Weaviate
- Qdrant
- Oracle
- Teradata
- SQLite
- Presto
- +14 more
Kestra
- Ansible
- dbt
- Spark
- Dremio
- Arrow Flight SQL
- Git
- GitHub Actions
- Terraform
- S3
- Azure Data Lake Storage
- Postgres
- JDBC databases
- HTTP APIs
- Polars
- Python
- Bash
- Node.js
- Go
- Google Gemini
- Perplexity
- Google Analytics
- Facebook Ads
- RabbitMQ
- Yahoo Finance
- +9 more
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.