Apache Airflow is a mature, open-source workflow orchestration platform with a larger community and extensive integrations, while Prefect is a modern alternative offering simpler syntax, better error handling, and a managed cloud option with a steeper learning curve for traditional DevOps teams.
Apache Airflow vs Prefect — Side-by-side comparison on A Versus B
Open-source workflow orchestration platform for data pipelines using task-based DAGs
Modern Python-based workflow orchestration with automatic retry logic, improved error handling, and optional managed cloud platform.
Learning Curve. Community Size. Managed Cloud Offering. Error Handling & Retries. Installation Complexity. Production Usage Market Share. Native Task Dependencies
Choose Apache Airflow if you need proven production stability, the largest ecosystem of integrations (1,000+), strong community support, and work in enterprise environments where it's already standardized. Choose Prefect if you prioritize developer experience, want faster time-to-productivity, prefer a modern Python-first approach, need built-in cloud orchestration, or are starting a new project without legacy Airflow infrastructure.
Apache Airflow: 8-16 hours | Prefect: N/A
Apache Airflow: 10+ via adapters | Prefect: N/A
Apache Airflow: Intermediate to Advanced | Prefect: N/A
Apache Airflow: E, L, T, testing, ML, monitoring (full stack) | Prefect: N/A
Apache Airflow: High (scheduler, web server, worker, database required) | Prefect: N/A
Apache Airflow: 120 minutes | Prefect: 5 minutes
Apache Airflow: 50-70 lines | Prefect: 15-20 lines
Apache Airflow: 2,000+ operators | Prefect: 1,200+ providers
Apache Airflow: 4+ (scheduler, worker, DB, broker) | Prefect: Zero (fully managed)
Apache Airflow: 35,000+ stars | Prefect: 50,000+ stars
Apache Airflow: Self-hosted (varies) | Prefect: 99.9%
Apache Airflow: Community or third-party paid | Prefect: 24/7 SLA-backed support
Apache Airflow: Complex (DAG operators) | Prefect: Simple (decorator-based)
Apache Airflow: 9+ years (since 2015) | Prefect: N/A
Apache Airflow: Days (practical limit) | Prefect: N/A
Apache Airflow: Python (primary), Java/Go/C# (limited) | Prefect: N/A
Apache Airflow: 1,200+ official operators | Prefect: N/A
Apache Airflow: Manual retry + task checkpointing | Prefect: N/A
Apache Airflow: 5+ (scheduler, webserver, DB, executor, metadata) | Prefect: N/A
Apache Airflow: Yes (Astronomer, cloud providers) | Prefect: N/A
Apache Airflow: 9 years (2015) | Prefect: N/A
Apache Airflow: External tools required | Prefect: N/A
Apache Airflow: Minimal type hints, runtime validation | Prefect: N/A
Apache Airflow: Task-centric DAGs | Prefect: N/A
Estimated Learning Curve (Hours to Productivity)
Apache Airflow: 20-30 hours | Prefect: N/A
Apache Airflow: 1,800+ Providers | Prefect: N/A
Apache Airflow: 5-10 days | Prefect: N/A
Apache Airflow: 1-2 GB | Prefect: 150MB+ recommended
Apache Airflow: Yes (comprehensive) | Prefect: N/A
Apache Airflow: 500+ commits | Prefect: N/A
Apache Airflow: Yes (full support) | Prefect: Full support for runtime-determined dependencies
Apache Airflow: Yes (PostgreSQL/MySQL) | Prefect: N/A
Apache Airflow: 10,000-3,600,000 ms (10 seconds to 1 hour typical) | Prefect: N/A
Apache Airflow: ~1,000-5,000 tasks/min | Prefect: N/A
Apache Airflow: 5-15 minutes (quick setup) | Prefect: N/A
Apache Airflow: Fully native (DAG definitions in pure Python) | Prefect: N/A
Apache Airflow: At-least-once (with retries) | Prefect: N/A
Apache Airflow: Advanced (DAG viewer, logs, metrics, triggers) | Prefect: N/A
Apache Airflow: Java 8+ (optional; Python primary) | Prefect: N/A
Apache Airflow: Requires external components (Celery/Kubernetes/RabbitMQ) | Prefect: Built-in Prefect Cloud support
Apache Airflow: 8-12+ files (scheduler, executor, database, webserver configs) | Prefect: 1-2 files (API key, optional environment config)
Apache Airflow: Community-driven (paid support via third parties) | Prefect: $600-$3000/month (Prefect Cloud Team/Enterprise)
Apache Airflow: Manual configuration required | Prefect: Task-level only
Apache Airflow: Limited (runtime only) | Prefect: N/A
Apache Airflow: 250-400 MB | Prefect: N/A
Apache Airflow: 30-45 minutes | Prefect: N/A
Apache Airflow: Yes (comprehensive web UI included) | Prefect: N/A
Apache Airflow: Native DAG-based automatic resolution | Prefect: N/A
Apache Airflow: 3 (PostgreSQL, MySQL, SQLite) | Prefect: Built-in (Dask, RayCluster)
Setup Complexity (Configuration Files Required)
Apache Airflow: 5-7 (airflow.cfg, DAG files, connections, secrets, logging config) | Prefect: N/A
Apache Airflow: 45-90 minutes with PostgreSQL + webserver setup | Prefect: N/A
Apache Airflow: 15+ core features (DAG visualization, execution history, logs, task duration, SLAs, alerts, backfill) | Prefect: N/A
Apache Airflow: 200+ officially maintained operators + community operators | Prefect: N/A
Enterprise Adoption (Fortune 500 Users Reported)
Apache Airflow: Airbnb, Amazon, Google, Netflix, Twitter (estimated 80+ F500) | Prefect: N/A
Apache Airflow: 1 (PostgreSQL backend only, no message queue required) | Prefect: N/A
Apache Airflow: 500-800 MB baseline | Prefect: N/A
Community Repository Stars (as of Feb 2025)
Apache Airflow: 35,800 GitHub stars | Prefect: N/A
Apache Airflow: 50,000+ | Prefect: 5,000+
Apache Airflow: PostgreSQL/MySQL required | Prefect: SQLite (included)
Apache Airflow: 4-8 hours | Prefect: 15-30 minutes
Apache Airflow: Manual configuration | Prefect: Built-in exponential backoff
Apache Airflow: No (third-party only) | Prefect: Yes (Prefect Cloud)
Apache Airflow: Task-level only (limited) | Prefect: N/A
Apache Airflow: Minimal (manual validation) | Prefect: N/A
Apache Airflow: 6-8 weeks to proficiency | Prefect: N/A
Apache Airflow: Astronomer Cloud (third-party) | Prefect: N/A
Apache Airflow: 2M+ (proven in production) | Prefect: N/A
Apache Airflow: N/A | Prefect: 10-15 minutes
Apache Airflow: N/A | Prefect: 6 years (2018-present)
Apache Airflow: N/A | Prefect: Yes (first-class)
Apache Airflow: N/A | Prefect: Yes (Prefect Cloud native)
Apache Airflow: N/A | Prefect: No (optional)
Apache Airflow: N/A | Prefect: Native implementation
Apache Airflow: N/A | Prefect: Python 3.7+
Apache Airflow: N/A | Prefect: 12% of orchestration users
Apache Airflow: N/A | Prefect: 80+ integrations
Apache Airflow: N/A | Prefect: $0 (unlimited runs)
Apache Airflow: N/A | Prefect: 1 second (any interval)
Apache Airflow: N/A | Prefect: 12-16 hours (setup + orchestration logic)
Apache Airflow: N/A | Prefect: Manual documentation via Prefect UI and docstrings
Apache Airflow: N/A | Prefect: Python 3.8
Apache Airflow: N/A | Prefect: 15-20 minutes
Apache Airflow: N/A | Prefect: No - requires external tools
Apache Airflow: N/A | Prefect: 8+ (K8s, Docker, serverless)
Apache Airflow: N/A | Prefect: Free for self-hosted, $50/month for Prefect Cloud
Apache Airflow: N/A | Prefect: ~2,500 companies
Apache Airflow: N/A | Prefect: Python (with SQL support)
Apache Airflow: N/A | Prefect: $0 (unlimited for Prefect Cloud free tier)
Apache Airflow: N/A | Prefect: No native framework—requires external tools
Apache Airflow: N/A | Prefect: 4-8 hours
Apache Airflow: N/A | Prefect: K8s, Docker, VMs, Serverless, On-premise
Apache Airflow: N/A | Prefect: 1 (extensible integrations)
Apache Airflow: N/A | Prefect: Prefect Cloud with SLA support tiers
Apache Airflow: N/A | Prefect: Open-source + Prefect Cloud (starts $299/month)
Apache Airflow: N/A | Prefect: Python decorators and native code
Apache Airflow: N/A | Prefect: 2-4 weeks
How to choose between Apache Airflow and Prefect
Apache Airflow vs Prefect — Structured Comparison Data
Machine-readable comparison dataset for Apache Airflow vs Prefect. Contains 122 attribute comparisons, 5 FAQ pairs.
Apache Airflow vs Prefect — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Apache Airflow vs Prefect.
Prefect is significantly easier for Python developers new to workflow orchestration. It uses standard Python decorators (@flow, @task) requiring minimal boilerplate, while Airflow requires understanding the DAG (Directed Acyclic Graph) programming model, which adds conceptual overhead. Most developers can write their first Prefect workflow in 30 minutes vs 2-4 hours for Airflow.
Which requires more infrastructure management?
Airflow requires substantial infrastructure: a metadata database (PostgreSQL/MySQL), scheduler, webserver, and worker processes must all be deployed and maintained. Prefect can run standalone with SQLite, though Prefect Cloud (managed SaaS) eliminates infrastructure entirely. For production, Airflow typically requires 2-3 dedicated team members for DevOps; Prefect Cloud requires zero.
Apache Airflow dominates with 1,000+ pre-built operators covering major cloud providers (AWS, GCP, Azure), data warehouses (Snowflake, BigQuery, Redshift), and tools (Spark, Kubernetes, Salesforce). Prefect has ~200 integrations. However, both platforms allow custom integrations; the difference is the ecosystem maturity for common enterprise tools.
Airflow is free but has significant operational costs: self-hosting requires infrastructure ($500-2,000/month for dedicated servers). Prefect is free (open-source), but Prefect Cloud charges $0.10 per million task runs or $600-3,000+/month for team plans. Airflow has no licensing fees but higher DevOps costs; Prefect Cloud has lower operational overhead but recurring software costs.
Which is better for real-time vs batch workflows?
Both handle batch workflows well (daily/hourly jobs). For real-time event-driven workflows, Prefect's built-in error handling and simpler Python syntax make it easier to implement complex retry logic and dynamic task generation. Airflow can handle this but requires more custom code. For sub-second scheduling needs, neither is optimal; consider Apache Kafka or Apache Flink instead.
How to Choose Between Apache Airflow and Prefect
Learning Curve: Apache Airflow has Steeper - requires DAG programming model, while Prefect has Gentler - Pythonic, decorators-based approach.
Community Size: Apache Airflow has 50,000+ GitHub stars, 5,000+ contributors, while Prefect has 5,000+ GitHub stars, 300+ contributors.
Managed Cloud Offering: Apache Airflow has No official managed service, while Prefect has Prefect Cloud - fully managed SaaS.
Error Handling & Retries: Apache Airflow has Manual configuration required, while Prefect has Built-in automatic retry logic with exponential backoff.
Installation Complexity: Apache Airflow has Requires metadata database (PostgreSQL/MySQL), while Prefect has Works out-of-box with SQLite.
Production Usage Market Share: Apache Airflow has 72% of enterprises using workflow orchestration, while Prefect has 12% of enterprises using workflow orchestration.
Native Task Dependencies: Apache Airflow has Complex DAG syntax, while Prefect has Simple Python function calls.