Data Engineering Path · Airflow
The Airflow Ecosystem & Version Evolution
From Airbnb to Apache — The Journey of Airflow
Airflow's evolution from a single-company project to the most widely adopted workflow orchestrator in the world is a remarkable open-source success story. Understanding this evolution helps you make the right version and architecture decisions.
Timeline of Apache Airflow
flowchart TD
subgraph S1["Origins"]
direction LR
A["2014\nCreated at Airbnb"] --> B["2015\nOpen-sourced"] --> C["2016\nApache Incubator"]
end
subgraph S2["Maturity"]
direction LR
D["2019\nApache Top-Level Project"] --> E["2020\nAirflow 2.0 - TaskFlow API"]
end
subgraph S3["Recent"]
direction LR
F["2022-2024\nDynamic Task Mapping, Datasets"] --> G["2025\nAirflow 3.0 - New SDK, Assets"]
end
S1 --> S2 --> S3
style A fill:#00ad46,stroke:#00802f,color:#fff
style B fill:#00ad46,stroke:#00802f,color:#fff
style C fill:#00ad46,stroke:#00802f,color:#fff
style D fill:#017cee,stroke:#0159a3,color:#fff
style E fill:#017cee,stroke:#0159a3,color:#fff
style F fill:#8c4fff,stroke:#6a2fcc,color:#fff
style G fill:#8c4fff,stroke:#6a2fcc,color:#fff
Version Comparison
| Feature | Airflow 1.x | Airflow 2.x | Airflow 3.x |
|---|---|---|---|
| DAG Authoring | Classic operators only | TaskFlow API + Classic | New SDK (airflow.sdk) |
| Scheduler | Single-threaded, slow | High-performance, HA | Enhanced with multi-deployment |
| UI | Tree & Graph views | Grid View, improved | React-based modern UI |
| Task Mapping | Not available | Dynamic Task Mapping | Improved dynamic tasks |
| Deferrable Operators | Not available | Available (2.2+) | Default behavior |
| REST API | Experimental | Stable REST API | Enhanced API surface |
| Security | Basic RBAC | Full RBAC | Enhanced RBAC + multi-tenant |
| Providers | Bundled in core | Separate provider packages | Independent versioning |
| Python Support | 2.7 / 3.x | 3.7+ | 3.9+ |
Note
If you're starting a new project, always use the latest Airflow 2.x or 3.x release. Airflow 1.x is end-of-life and should be migrated. The TaskFlow API in 2.x/3.x dramatically simplifies DAG development.
If you're starting a new project, always use the latest Airflow 2.x or 3.x release. Airflow 1.x is end-of-life and should be migrated. The TaskFlow API in 2.x/3.x dramatically simplifies DAG development.
The Provider Ecosystem
One of Airflow's greatest strengths is its provider package system. Instead of bundling every connector in the core, each technology has its own independently versioned package:
| Provider Package | Technologies Covered | Install Command |
|---|---|---|
apache-airflow-providers-amazon |
S3, Redshift, Glue, EMR, Lambda, SageMaker, Athena | pip install apache-airflow-providers-amazon |
apache-airflow-providers-google |
BigQuery, GCS, Dataflow, Dataproc, Cloud Composer | pip install apache-airflow-providers-google |
apache-airflow-providers-microsoft-azure |
Blob Storage, Data Factory, Synapse, Azure ML | pip install apache-airflow-providers-microsoft-azure |
apache-airflow-providers-snowflake |
Snowflake warehouse & stages | pip install apache-airflow-providers-snowflake |
apache-airflow-providers-databricks |
Databricks jobs, notebooks, SQL | pip install apache-airflow-providers-databricks |
apache-airflow-providers-apache-spark |
Spark Submit, JDBC, Kubernetes | pip install apache-airflow-providers-apache-spark |
apache-airflow-providers-postgres |
PostgreSQL database | pip install apache-airflow-providers-postgres |
apache-airflow-providers-slack |
Slack notifications & webhooks | pip install apache-airflow-providers-slack |
Tip
You can browse all 80+ available providers at https://airflow.apache.org/docs/. Each provider has its own documentation, changelog, and version history. Install only the providers you need to keep your deployment lean.
You can browse all 80+ available providers at https://airflow.apache.org/docs/. Each provider has its own documentation, changelog, and version history. Install only the providers you need to keep your deployment lean.
Managed Airflow Services
For production deployments, many organizations use managed Airflow services:
| Service | Provider | Key Benefits |
|---|---|---|
| Cloud Composer | Google Cloud | Fully managed, integrated with GCP services |
| MWAA | Amazon Web Services | Managed Workflows for Apache Airflow |
| Astronomer | Astronomer Inc. | Enterprise platform, Astro CLI, deployment tooling |
| Azure Data Factory | Microsoft Azure | Managed orchestration (uses Airflow underneath) |
Important
Managed services abstract away infrastructure management but may lag behind the latest Airflow releases. Always check which Airflow version your managed service supports before relying on new features.
Managed services abstract away infrastructure management but may lag behind the latest Airflow releases. Always check which Airflow version your managed service supports before relying on new features.