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Apache Airflow

Free

Industry-standard workflow orchestration for data and ML pipelines.

Open SourceCloudSelf-hostedEnterprisePython SDK

Tool Info

Categories
Data Engineering · Workflow Automation
Developer
Apache Software Foundation
License
Open Source
Official Website
airflow.apache.org
Repository
apache/airflow
Official Docs

Overview

Apache Airflow schedules and monitors batch workflows as directed acyclic graphs.

It is the most widely deployed orchestrator in data engineering.

Common for RAG indexing jobs and ML batch pipelines.

Features

  • DAG-based workflows
  • Rich operator ecosystem
  • Scheduling
  • Managed providers

Pricing

Free tier available
Free (open source)Managed (Astronomer, etc.)

Pros

  • Industry standard
  • Huge operator library
  • Proven at scale

Best For

Batch data pipelinesML training schedulesLegacy orchestration

When NOT to Use

  • Operational overhead
  • Not asset-centric like Dagster

Typical Users

Data engineersML engineers

Related Tools

Apache Spark
Unified analytics engine for large-scale data processing and ML workloads.
Apache Flink
Stream-first data processing engine for real-time analytics and event pipelines.
dbt
Transform data in your warehouse using version-controlled SQL models.

Alternatives

Dagster
Data orchestrator for building, testing, and monitoring ML and AI pipelines.
Prefect
Modern Python workflow orchestration with dynamic execution and observability.
Kestra
Open-source orchestration platform for data, infrastructure, and business workflows.

Tags

#data#orchestration#workflow

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