Apache Airflow vs Kestra
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.
Kestra
A language-agnostic platform that lets teams define and run business-critical workflows declaratively as code, with built-in scheduling, event-driven triggers, retries, failure handling, and full observability across cloud, on-premise, and air-gapped deployments.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Kestra
- Open SourceFree
- Kestra CloudManaged cloud with enterprise support
- Fully Managed Platform (Hosting, Upgrades, Monitoring)
- Built-in Security and Governance Features
- Customer Success Program & Enterprise Support with SLA
- Audit Logs
- Kestra EnterpriseContact sales
- Run anywhere Cloud, On-Prem, Air-Gapped
- RBAC, audit logs, secrets management, asset lineage
- AI Copilot (Any LLM Cloud or Self-Hosted)
- Human-in-the-Loop Approvals
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.
- Google Cloud Platform
- Slack
- Salesforce
- PostgreSQL
- MySQL
- Kubernetes
- Docker
- Apache Spark
- Apache Kafka
- Elasticsearch
- Datadog
- GitHub
- OpenAI
- Anthropic
- Airbyte
- PagerDuty
Apache Airflow
Leader- Amazon Web Services
- Microsoft Azure
- Databricks
- Snowflake
- dbt Cloud
- Tableau
- MongoDB
- Redis
- Apache Cassandra
- Apache Flink
- Apache Druid
- Jenkins
- Cohere
- Pinecone
- Weaviate
- Qdrant
- Oracle
- Teradata
- SQLite
- Presto
- Trino
- ClickHouse
- Neo4j
- Informatica
- +21 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
- +18 more
Apache Airflow or Kestra: 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.