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Apache Airflow vs Kestra

Apache Airflow

airflow.apache.org

Kestra

kestra.io

Side by side

FigureApache AirflowKestra
Price fromFreeFree
Free planYesYes
Free trial—Yes
Open source—Yes
WebYesYes
Windows—Yes
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published14
Spec score · Workload Automation Software8.6 (#4)8.6 (#6)
Spec score · Workflow Orchestration Software8.6 (#8)8.6 (#10)
Spec score · DataOps Platforms8.6 (#5)8.6 (#6)

Plans

Apache Airflow

  • Apache AirflowFree

Apache Airflow pricing →

Kestra

  • Open SourceFree
  • Enterprise EditionPriced on request
  • Kestra CloudPriced on request
  • Kestra CloudPriced on request

Kestra pricing →

In their own words

Apache Airflow

Apache Airflow is a platform for authoring, scheduling, and monitoring workflows written in Python. It is designed for batch workflows with a defined beginning and end that run on a schedule. Its web application lets users manage and schedule workflows, trigger DAGs manually, inspect task status and logs, backfill runs, and rerun failed tasks. A modular architecture uses a message queue to coordinate workers and can orchestrate an arbitrary number of them. Built-in operators connect workflows to Google Cloud Platform, Amazon Web Services, Microsoft Azure, and other services. The community maintains more than 80 separately installable provider packages, which can be upgraded or downgraded independently of Airflow core. Airflow can read connections, variables, and configuration from secret backends, but those integrations do not support writes. JWT authentication is used for its public REST API and internal Execution API. From Airflow 3 onward, sensitive credentials are masked in logs, the interface, and API output. Airflow is free to download and use under the Apache License.

Visit airflow.apache.org

Kestra

Kestra is a declarative orchestration platform for building, running, and governing workflows across an organization. Workflows, called flows, are defined in YAML and can combine tasks, dependencies, conditions, triggers, and runtime parameters. Execution controls include retries, failure policies, timeouts, concurrency limits, worker assignment, and log capture. Kestra advertises more than 2,000 plugins for connecting to external tools, with examples including Airbyte, AWS, Azure, BigQuery, dbt, Docker, GitHub, Kafka, Kubernetes, Slack, Snowflake, and Terraform. A flow can orchestrate SQL, Python, shell, APIs, Terraform, dbt, Spark, and custom tools. The platform includes an MCP server for AI agents and supports exposing flows as callable tools. Teams can self-host with Docker or Kubernetes; Enterprise Edition also supports cloud, on-premises, and air-gapped environments. Setup instructions cover macOS, Windows, and Linux, alongside web and API platforms. Kestra Cloud advertises up to two months free during team setup. The Open Source and Enterprise Edition plans have no price listed.

Visit kestra.io