Apache Airflow vs Prefect
type: Article
description: 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.
language: en-US
date published: 2026-07-08T03:03:13.950Z
date created: 2026-07-08T03:03:13.950Z
date modified: 2026-07-08T03:03:14.054Z
content reference time: 2026-07-08T03:03:14.054Z
author: A Versus B
publisher: A Versus B
about: Apache Airflow
about: Prefect
abstract: 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.
text: Learning Curve. Community Size. Managed Cloud Offering. Error Handling & Retries. Installation Complexity. Production Usage Market Share. Native Task Dependencies
conclusion text: 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.
additional property: Monthly PyPI/Package Downloads (2024)
  type: PropertyValue
  value: Apache Airflow: 2.8M | Prefect: N/A
additional property: Time to First Pipeline (expert user)
  type: PropertyValue
  value: Apache Airflow: 8-16 hours | Prefect: N/A
additional property: Native Data Warehouse Support
  type: PropertyValue
  value: Apache Airflow: 10+ via adapters | Prefect: N/A
additional property: Minimum Python Knowledge Required
  type: PropertyValue
  value: Apache Airflow: Intermediate to Advanced | Prefect: N/A
additional property: Open Source Contributors
  type: PropertyValue
  value: Apache Airflow: 1,200+ | Prefect: N/A
additional property: Core Use Case Scope
  type: PropertyValue
  value: Apache Airflow: E, L, T, testing, ML, monitoring (full stack) | Prefect: N/A
additional property: Infrastructure Setup Complexity
  type: PropertyValue
  value: Apache Airflow: High (scheduler, web server, worker, database required) | Prefect: N/A
additional property: Time to Production (First Workflow)
  type: PropertyValue
  value: Apache Airflow: 120 minutes | Prefect: 5 minutes
  value reference: Prefect
additional property: Lines of Code (Basic ETL Task)
  type: PropertyValue
  value: Apache Airflow: 50-70 lines | Prefect: 15-20 lines
  value reference: Prefect
additional property: Available Integrations
  type: PropertyValue
  value: Apache Airflow: 2,000+ operators | Prefect: 1,200+ providers
  value reference: Apache Airflow
additional property: Minimum Infrastructure Requirements
  type: PropertyValue
  value: Apache Airflow: 4+ (scheduler, worker, DB, broker) | Prefect: Zero (fully managed)
additional property: GitHub Stars (Community Indicator)
  type: PropertyValue
  value: Apache Airflow: 35,000+ stars | Prefect: 50,000+ stars
  value reference: Prefect
additional property: Uptime SLA (Managed Services)
  type: PropertyValue
  value: Apache Airflow: Self-hosted (varies) | Prefect: 99.9%
additional property: Enterprise Support Availability
  type: PropertyValue
  value: Apache Airflow: Community or third-party paid | Prefect: 24/7 SLA-backed support
additional property: Configuration as Code Simplicity
  type: PropertyValue
  value: Apache Airflow: Complex (DAG operators) | Prefect: Simple (decorator-based)
  value reference: Prefect
additional property: GitHub Stars (Community Maturity)
  type: PropertyValue
  value: Apache Airflow: 22,000+ | Prefect: N/A
additional property: Project Age
  type: PropertyValue
  value: Apache Airflow: 9+ years (since 2015) | Prefect: N/A
additional property: Maximum Workflow Duration
  type: PropertyValue
  value: Apache Airflow: Days (practical limit) | Prefect: N/A
additional property: Supported Programming Languages (SDKs)
  type: PropertyValue
  value: Apache Airflow: Python (primary), Java/Go/C# (limited) | Prefect: N/A
additional property: Pre-built Integrations/Operators
  type: PropertyValue
  value: Apache Airflow: 1,200+ official operators | Prefect: N/A
additional property: Fault Tolerance Method
  type: PropertyValue
  value: Apache Airflow: Manual retry + task checkpointing | Prefect: N/A
additional property: Minimum Deployment Complexity
  type: PropertyValue
  value: Apache Airflow: 5+ (scheduler, webserver, DB, executor, metadata) | Prefect: N/A
additional property: Enterprise Commercial Support Available
  type: PropertyValue
  value: Apache Airflow: Yes (Astronomer, cloud providers) | Prefect: N/A
additional property: Time Since First Release
  type: PropertyValue
  value: Apache Airflow: 9 years (2015) | Prefect: N/A
additional property: Pre-built Integrations
  type: PropertyValue
  value: Apache Airflow: 1,000+ | Prefect: 200+
  value reference: Apache Airflow
additional property: Built-in Data Quality Testing
  type: PropertyValue
  value: Apache Airflow: External tools required | Prefect: N/A
additional property: Type Safety & Validation
  type: PropertyValue
  value: Apache Airflow: Minimal type hints, runtime validation | Prefect: N/A
additional property: Data Lineage Model
  type: PropertyValue
  value: Apache Airflow: Task-centric DAGs | Prefect: N/A
additional property: Estimated Learning Curve (Hours to Productivity)
  type: PropertyValue
  value: Apache Airflow: 20-30 hours | Prefect: N/A
additional property: Active Contributors (Monthly)
  type: PropertyValue
  value: Apache Airflow: 150+ | Prefect: N/A
additional property: Native Integrations
  type: PropertyValue
  value: Apache Airflow: 1,800+ Providers | Prefect: N/A
additional property: Time to First Productive Workflow
  type: PropertyValue
  value: Apache Airflow: 5-10 days | Prefect: N/A
additional property: Minimum RAM Requirement
  type: PropertyValue
  value: Apache Airflow: 1-2 GB | Prefect: 150MB+ recommended
  value reference: Apache Airflow
additional property: Built-in Web Dashboard
  type: PropertyValue
  value: Apache Airflow: Yes (comprehensive) | Prefect: N/A
additional property: Annual Commit Activity
  type: PropertyValue
  value: Apache Airflow: 500+ commits | Prefect: N/A
additional property: Dynamic DAG Support
  type: PropertyValue
  value: Apache Airflow: Yes (full support) | Prefect: Full support for runtime-determined dependencies
additional property: External Database Required
  type: PropertyValue
  value: Apache Airflow: Yes (PostgreSQL/MySQL) | Prefect: N/A
additional property: Processing Latency
  type: PropertyValue
  value: Apache Airflow: 10,000-3,600,000 ms (10 seconds to 1 hour typical) | Prefect: N/A
additional property: Maximum Throughput per Node
  type: PropertyValue
  value: Apache Airflow: ~1,000-5,000 tasks/min | Prefect: N/A
additional property: Time to Deploy Pipeline
  type: PropertyValue
  value: Apache Airflow: 5-15 minutes (quick setup) | Prefect: N/A
additional property: Python Support Level
  type: PropertyValue
  value: Apache Airflow: Fully native (DAG definitions in pure Python) | Prefect: N/A
additional property: State Consistency Guarantee
  type: PropertyValue
  value: Apache Airflow: At-least-once (with retries) | Prefect: N/A
additional property: Integrated Web UI
  type: PropertyValue
  value: Apache Airflow: Advanced (DAG viewer, logs, metrics, triggers) | Prefect: N/A
additional property: Minimum Java Version Required
  type: PropertyValue
  value: Apache Airflow: Java 8+ (optional; Python primary) | Prefect: N/A
additional property: Initial Release
  type: PropertyValue
  value: Apache Airflow: 2014 | Prefect: 2018
  value reference: Prefect
additional property: Market Share Adoption
  type: PropertyValue
  value: Apache Airflow: 68% | Prefect: 12%
  value reference: Apache Airflow
additional property: Available Providers/Integrations
  type: PropertyValue
  value: Apache Airflow: 300+ | Prefect: 120+
  value reference: Apache Airflow
additional property: Time to Proficiency
  type: PropertyValue
  value: Apache Airflow: 40-80 | Prefect: 15-30
  value reference: Prefect
additional property: Cloud-Native Architecture
  type: PropertyValue
  value: Apache Airflow: Requires external components (Celery/Kubernetes/RabbitMQ) | Prefect: Built-in Prefect Cloud support
interactivity type: active
significant link: https://www.aversusb.net/entity/apache-airflow
significant link: https://www.aversusb.net/alternatives/apache-airflow
significant link: https://www.aversusb.net/entity/prefect
significant link: https://www.aversusb.net/alternatives/prefect
significant link: https://www.aversusb.net/api/answer/airflow-vs-prefect)
significant link: https://www.aversusb.net/api/v1/schema/airflow-vs-prefect)
related link: https://www.aversusb.net/compare/prefect-vs-airflow
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teaches: How to choose between Apache Airflow and Prefect
genre: Software

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width: 1200
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caption: Apache Airflow vs Prefect — Side-by-side comparison on A Versus B

A Versus B
type: Organization

Apache Airflow
type: SoftwareApplication
alternate name: AA
language: en-US
description: Open-source workflow orchestration platform for data pipelines using task-based DAGs
image: ImageObject
  caption: Apache Airflow
subject of: Apache Airflow vs Prefect
image: ImageObject
  caption: Apache Airflow

Prefect
type: SoftwareApplication
language: en-US
description: Modern Python-based workflow orchestration with automatic retry logic, improved error handling, and optional managed cloud platform.
image: ImageObject
  caption: Prefect
subject of: Apache Airflow vs Prefect
image: ImageObject
  caption: Prefect

Apache Airflow vs Prefect — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Apache Airflow vs Prefect. Contains 122 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: JSON-LD knowledge graph
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variable measured: Time to Deploy First Task (Minutes)
variable measured: Web UI Completeness
variable measured: Supported Task Types / Operators
variable measured: Enterprise Adoption (Fortune 500 Users Reported)
variable measured: Default Message Broker Options
is based on: https://www.aversusb.net/compare/airflow-vs-prefect)

Apache Airflow vs Prefect — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Apache Airflow vs Prefect.
has defined term: Adoption
has defined term: Ease of Use
has defined term: Integration
has defined term: Accessibility
has defined term: Community
has defined term: Functionality
has defined term: Operations
has defined term: Deployment & Setup
has defined term: Development
has defined term: Ecosystem
has defined term: Infrastructure
has defined term: Reliability
has defined term: Support
has defined term: Adoption & Community
has defined term: Maturity
has defined term: Capability
has defined term: Language Support
has defined term: Extensibility
has defined term: Integrations
has defined term: Features
has defined term: Developer Experience
has defined term: Architecture
has defined term: Onboarding
has defined term: Community Activity
has defined term: Development Activity
has defined term: Features & Ecosystem
has defined term: System Requirements
has defined term: Performance
has defined term: Data Reliability
has defined term: Monitoring
has defined term: Requirements
has defined term: Usability
has defined term: Setup
has defined term: Community Support
has defined term: Flexibility
has defined term: Deployment
has defined term: Installation
has defined term: Market
has defined term: Data Governance
has defined term: Performance & Scale
has defined term: Cost
has defined term: Stability
has defined term: History
has defined term: Observability
has defined term: Compatibility
has defined term: Integration Scope
has defined term: Pricing
has defined term: Operational Flexibility
has defined term: Deployment Speed
has defined term: Documentation
has defined term: Community & Adoption
has defined term: Technical Stack
has defined term: ML Capabilities
has defined term: Time to Production

Adoption
type: DefinedTerm
term code: adoption
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Accessibility
type: DefinedTerm
term code: accessibility
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Functionality
type: DefinedTerm
term code: functionality
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Operations
type: DefinedTerm
term code: operations
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Deployment & Setup
type: DefinedTerm
term code: deployment-&-setup
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Development
type: DefinedTerm
term code: development
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Infrastructure
type: DefinedTerm
term code: infrastructure
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Support
type: DefinedTerm
term code: support
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Adoption & Community
type: DefinedTerm
term code: adoption-&-community
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Maturity
type: DefinedTerm
term code: maturity
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Capability
type: DefinedTerm
term code: capability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Language Support
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term code: language-support
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Extensibility
type: DefinedTerm
term code: extensibility
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Integrations
type: DefinedTerm
term code: integrations
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Features
type: DefinedTerm
term code: features
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Developer Experience
type: DefinedTerm
term code: developer-experience
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Architecture
type: DefinedTerm
term code: architecture
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Onboarding
type: DefinedTerm
term code: onboarding
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Community Activity
type: DefinedTerm
term code: community-activity
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Development Activity
type: DefinedTerm
term code: development-activity
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Features & Ecosystem
type: DefinedTerm
term code: features-&-ecosystem
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

System Requirements
type: DefinedTerm
term code: system-requirements
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Performance
type: DefinedTerm
term code: performance
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Data Reliability
type: DefinedTerm
term code: data-reliability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Monitoring
type: DefinedTerm
term code: monitoring
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Requirements
type: DefinedTerm
term code: requirements
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Setup
type: DefinedTerm
term code: setup
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Community Support
type: DefinedTerm
term code: community-support
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Flexibility
type: DefinedTerm
term code: flexibility
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Installation
type: DefinedTerm
term code: installation
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Market
type: DefinedTerm
term code: market
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Data Governance
type: DefinedTerm
term code: data-governance
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Performance & Scale
type: DefinedTerm
term code: performance-&-scale
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Cost
type: DefinedTerm
term code: cost
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Stability
type: DefinedTerm
term code: stability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

History
type: DefinedTerm
term code: history
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Observability
type: DefinedTerm
term code: observability
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Compatibility
type: DefinedTerm
term code: compatibility
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Integration Scope
type: DefinedTerm
term code: integration-scope
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Pricing
type: DefinedTerm
term code: pricing
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Operational Flexibility
type: DefinedTerm
term code: operational-flexibility
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Deployment Speed
type: DefinedTerm
term code: deployment-speed
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Documentation
type: DefinedTerm
term code: documentation
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Community & Adoption
type: DefinedTerm
term code: community-&-adoption
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Technical Stack
type: DefinedTerm
term code: technical-stack
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

ML Capabilities
type: DefinedTerm
term code: ml-capabilities
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

Time to Production
type: DefinedTerm
term code: time-to-production
in defined term set: Apache Airflow vs Prefect — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T03:03:14.054Z
author: A Versus B
publisher: A Versus B
is part of: airflow-vs-prefect)
main entity: Which is easier to learn for beginners?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: Which requires more infrastructure management?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: Which has better integration support?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: What are the cost differences?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: Which is better for real-time vs batch workflows?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US

How to Choose Between Apache Airflow and Prefect
type: HowTo
description: 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.
language: en-US
total time: PT3M
step: Consider: Learning Curve
step: Consider: Community Size
step: Consider: Managed Cloud Offering
step: Consider: Error Handling & Retries
step: Consider: Installation Complexity
step: Consider: Production Usage Market Share
step: Consider: Native Task Dependencies
tool: A Versus B Comparison Guide
tip: HowToTip
  text: 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.

Consider: Learning Curve
type: HowToStep
position: 1
text: Learning Curve: Apache Airflow has Steeper - requires DAG programming model, while Prefect has Gentler - Pythonic, decorators-based approach.

Consider: Community Size
type: HowToStep
position: 2
text: Community Size: Apache Airflow has 50,000+ GitHub stars, 5,000+ contributors, while Prefect has 5,000+ GitHub stars, 300+ contributors.

Consider: Managed Cloud Offering
type: HowToStep
position: 3
text: Managed Cloud Offering: Apache Airflow has No official managed service, while Prefect has Prefect Cloud - fully managed SaaS.

Consider: Error Handling & Retries
type: HowToStep
position: 4
text: Error Handling & Retries: Apache Airflow has Manual configuration required, while Prefect has Built-in automatic retry logic with exponential backoff.

Consider: Installation Complexity
type: HowToStep
position: 5
text: Installation Complexity: Apache Airflow has Requires metadata database (PostgreSQL/MySQL), while Prefect has Works out-of-box with SQLite.

Consider: Production Usage Market Share
type: HowToStep
position: 6
text: Production Usage Market Share: Apache Airflow has 72% of enterprises using workflow orchestration, while Prefect has 12% of enterprises using workflow orchestration.

Consider: Native Task Dependencies
type: HowToStep
position: 7
text: Native Task Dependencies: Apache Airflow has Complex DAG syntax, while Prefect has Simple Python function calls.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Apache Airflow vs Prefect
review body: 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.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Apache Airflow vs Prefect

Minimum Setup Complexity
type: PropertyValue
value: Apache Airflow: 8-12+ files (scheduler, executor, database, webserver configs) | Prefect: 1-2 files (API key, optional environment config)
value reference: Prefect

Enterprise Support Plans
type: PropertyValue
value: Apache Airflow: Community-driven (paid support via third parties) | Prefect: $600-$3000/month (Prefect Cloud Team/Enterprise)

First Release Year
type: PropertyValue
value: Apache Airflow: 2014 | Prefect: N/A

Production Deployments (estimated)
type: PropertyValue
value: Apache Airflow: 50,000+ | Prefect: N/A

Built-in Data Lineage
type: PropertyValue
value: Apache Airflow: Manual configuration required | Prefect: Task-level only

Provider/Integration Count
type: PropertyValue
value: Apache Airflow: 350+ | Prefect: N/A

Type Safety Support
type: PropertyValue
value: Apache Airflow: Limited (runtime only) | Prefect: N/A

Minimum Python Version
type: PropertyValue
value: Apache Airflow: 3.8+ | Prefect: N/A

Community Slack Members
type: PropertyValue
value: Apache Airflow: 15,000+ | Prefect: N/A

Memory Usage at Idle
type: PropertyValue
value: Apache Airflow: 250-400 MB | Prefect: N/A

Setup Time for Hello World
type: PropertyValue
value: Apache Airflow: 30-45 minutes | Prefect: N/A

Built-in UI/Dashboard
type: PropertyValue
value: Apache Airflow: Yes (comprehensive web UI included) | Prefect: N/A

Task Dependency Management
type: PropertyValue
value: Apache Airflow: Native DAG-based automatic resolution | Prefect: N/A

Supported Message Brokers
type: PropertyValue
value: Apache Airflow: 3 (PostgreSQL, MySQL, SQLite) | Prefect: Built-in (Dask, RayCluster)
value reference: Apache Airflow

Setup Complexity (Configuration Files Required)
type: PropertyValue
value: Apache Airflow: 5-7 (airflow.cfg, DAG files, connections, secrets, logging config) | Prefect: N/A

Time to Deploy First Task (Minutes)
type: PropertyValue
value: Apache Airflow: 45-90 minutes with PostgreSQL + webserver setup | Prefect: N/A

Web UI Completeness
type: PropertyValue
value: Apache Airflow: 15+ core features (DAG visualization, execution history, logs, task duration, SLAs, alerts, backfill) | Prefect: N/A

Supported Task Types / Operators
type: PropertyValue
value: Apache Airflow: 200+ officially maintained operators + community operators | Prefect: N/A

Enterprise Adoption (Fortune 500 Users Reported)
type: PropertyValue
value: Apache Airflow: Airbnb, Amazon, Google, Netflix, Twitter (estimated 80+ F500) | Prefect: N/A

Default Message Broker Options
type: PropertyValue
value: Apache Airflow: 1 (PostgreSQL backend only, no message queue required) | Prefect: N/A

Minimum Memory Per Worker (MB)
type: PropertyValue
value: Apache Airflow: 500-800 MB baseline | Prefect: N/A

Community Repository Stars (as of Feb 2025)
type: PropertyValue
value: Apache Airflow: 35,800 GitHub stars | Prefect: N/A

GitHub Stars
type: PropertyValue
value: Apache Airflow: 50,000+ | Prefect: 5,000+
value reference: Apache Airflow

Active Contributors
type: PropertyValue
value: Apache Airflow: 5,000+ | Prefect: 300+
value reference: Apache Airflow

Minimum Database Setup
type: PropertyValue
value: Apache Airflow: PostgreSQL/MySQL required | Prefect: SQLite (included)

Enterprise Production Adoption
type: PropertyValue
value: Apache Airflow: 72% | Prefect: 12%
value reference: Apache Airflow

Base Setup Time
type: PropertyValue
value: Apache Airflow: 4-8 hours | Prefect: 15-30 minutes
value reference: Prefect

Native Retry Logic
type: PropertyValue
value: Apache Airflow: Manual configuration | Prefect: Built-in exponential backoff

Managed Cloud Option Available
type: PropertyValue
value: Apache Airflow: No (third-party only) | Prefect: Yes (Prefect Cloud)

GitHub Stars (Community Size)
type: PropertyValue
value: Apache Airflow: 36,000+ | Prefect: N/A

Built-in Provider Integrations
type: PropertyValue
value: Apache Airflow: 300+ | Prefect: N/A

First Official Release
type: PropertyValue
value: Apache Airflow: 2014 | Prefect: N/A

Native Asset Lineage Tracking
type: PropertyValue
value: Apache Airflow: Task-level only (limited) | Prefect: N/A

Type Safety Features
type: PropertyValue
value: Apache Airflow: Minimal (manual validation) | Prefect: N/A

Learning Curve Time (Average)
type: PropertyValue
value: Apache Airflow: 6-8 weeks to proficiency | Prefect: N/A

Enterprise SaaS Option Available
type: PropertyValue
value: Apache Airflow: Astronomer Cloud (third-party) | Prefect: N/A

Maximum Daily Task Executions (Tested)
type: PropertyValue
value: Apache Airflow: 2M+ (proven in production) | Prefect: N/A

Setup Time (Basic)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 10-15 minutes

Cloud Pricing (Task Runs)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: $0.30

Project Maturity (Years Active)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 6 years (2018-present)

Kubernetes Native Support
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Yes (first-class)

First Release
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 2018

Setup Complexity (1-10)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 4

Built-in Monitoring Dashboard
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Yes (Prefect Cloud native)

Message Broker Required
type: PropertyValue
value: Apache Airflow: N/A | Prefect: No (optional)

Automatic Retry Logic
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Native implementation

Python Version Support (min)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Python 3.7+

Industry Adoption Rate
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 12% of orchestration users

Supported Data Warehouses/Databases
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 80+ integrations

Minimum Free Cloud Tier Monthly Cost
type: PropertyValue
value: Apache Airflow: N/A | Prefect: $0 (unlimited runs)

Scheduling Minimum Interval
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 1 second (any interval)

Time to First Production Pipeline
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 12-16 hours (setup + orchestration logic)

Documentation Automation
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Manual documentation via Prefect UI and docstrings

Minimum Python Version Supported
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Python 3.8

Time to First Pipeline (learning curve)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 15-20 minutes

Native Data Quality Checks
type: PropertyValue
value: Apache Airflow: N/A | Prefect: No - requires external tools

Deployment Configurations Supported
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 8+ (K8s, Docker, serverless)

SaaS Pricing (base tier)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Free for self-hosted, $50/month for Prefect Cloud

First Release Date
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 2018

GitHub Stars (2024)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 11,000

Estimated Active Users
type: PropertyValue
value: Apache Airflow: N/A | Prefect: ~2,500 companies

Primary Language
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Python (with SQL support)

Supported Data Warehouse Adapters
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 70+

Minimum Setup Time (Local)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 15-20 minutes

Free Cloud Tier Limit
type: PropertyValue
value: Apache Airflow: N/A | Prefect: $0 (unlimited for Prefect Cloud free tier)

Built-in Testing Framework
type: PropertyValue
value: Apache Airflow: N/A | Prefect: No native framework—requires external tools

Setup Time (Baseline)
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 4-8 hours

Infrastructure Flexibility
type: PropertyValue
value: Apache Airflow: N/A | Prefect: K8s, Docker, VMs, Serverless, On-premise

Native ML Features Count
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 1 (extensible integrations)

Commercial Support Tier
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Prefect Cloud with SLA support tiers

License Cost
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Open-source + Prefect Cloud (starts $299/month)

DAG Creation Method
type: PropertyValue
value: Apache Airflow: N/A | Prefect: Python decorators and native code

Typical Enterprise Deployment Time
type: PropertyValue
value: Apache Airflow: N/A | Prefect: 2-4 weeks

SpeakableSpecification
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Apache Airflow — Wikipedia
type: CreativeWork

Prefect — Wikipedia
type: CreativeWork

Compare Apache Airflow vs Prefect
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/airflow-vs-prefect)
object: Apache Airflow
object: Prefect

Built-in UI/Dashboard
type: PropertyValue
value reference: Monitoring

Task Dependency Management
type: PropertyValue
value reference: Features

Supported Message Brokers
type: PropertyValue
value reference: Flexibility

Setup Complexity (Configuration Files Required)
type: PropertyValue
value reference: Deployment

Time to Deploy First Task (Minutes)
type: PropertyValue
value reference: Deployment

Web UI Completeness
type: PropertyValue
value reference: Monitoring

Supported Task Types / Operators
type: PropertyValue
value reference: Functionality

Enterprise Adoption (Fortune 500 Users Reported)
type: PropertyValue
value reference: Adoption

Default Message Broker Options
type: PropertyValue
value reference: Architecture

Minimum Memory Per Worker (MB)
type: PropertyValue
value reference: Performance

Community Repository Stars (as of Feb 2025)
type: PropertyValue
value reference: Community

GitHub Stars
type: PropertyValue
value reference: Community

Active Contributors
type: PropertyValue
value reference: Community

Minimum Database Setup
type: PropertyValue
value reference: Installation

Enterprise Production Adoption
type: PropertyValue
value reference: Market

Base Setup Time
type: PropertyValue
value reference: Installation

Native Retry Logic
type: PropertyValue
value reference: Features

Managed Cloud Option Available
type: PropertyValue
value reference: Deployment

GitHub Stars (Community Size)
type: PropertyValue
value reference: Community

Built-in Provider Integrations
type: PropertyValue
value reference: Ecosystem

First Official Release
type: PropertyValue
value reference: Maturity

Native Asset Lineage Tracking
type: PropertyValue
value reference: Data Governance

Type Safety Features
type: PropertyValue
value reference: Developer Experience

Learning Curve Time (Average)
type: PropertyValue
value reference: Developer Experience

Enterprise SaaS Option Available
type: PropertyValue
value reference: Deployment

Maximum Daily Task Executions (Tested)
type: PropertyValue
value reference: Performance & Scale

Setup Time (Basic)
type: PropertyValue
value reference: Ease of Use

Cloud Pricing (Task Runs)
type: PropertyValue
value reference: Cost

Project Maturity (Years Active)
type: PropertyValue
value reference: Stability

Kubernetes Native Support
type: PropertyValue
value reference: Integration

First Release
type: PropertyValue
value reference: History

Setup Complexity (1-10)
type: PropertyValue
value reference: Ease of Use

Built-in Monitoring Dashboard
type: PropertyValue
value reference: Observability

Message Broker Required
type: PropertyValue
value reference: Infrastructure

Automatic Retry Logic
type: PropertyValue
value reference: Reliability

Python Version Support (min)
type: PropertyValue
value reference: Compatibility

Industry Adoption Rate
type: PropertyValue
value reference: Market

Supported Data Warehouses/Databases
type: PropertyValue
value reference: Integration Scope

Minimum Free Cloud Tier Monthly Cost
type: PropertyValue
value reference: Pricing

Scheduling Minimum Interval
type: PropertyValue
value reference: Operational Flexibility

Time to First Production Pipeline
type: PropertyValue
value reference: Deployment Speed

Documentation Automation
type: PropertyValue
value reference: Documentation

Minimum Python Version Supported
type: PropertyValue
value reference: Compatibility

Time to First Pipeline (learning curve)
type: PropertyValue
value reference: Ease of Use

Native Data Quality Checks
type: PropertyValue
value reference: Data Governance

Deployment Configurations Supported
type: PropertyValue
value reference: Deployment

SaaS Pricing (base tier)
type: PropertyValue
value reference: Pricing

First Release Date
type: PropertyValue
value reference: Maturity

GitHub Stars (2024)
type: PropertyValue
value reference: Community & Adoption

Estimated Active Users
type: PropertyValue
value reference: Community

Primary Language
type: PropertyValue
value reference: Technical Stack

Supported Data Warehouse Adapters
type: PropertyValue
value reference: Integration

Minimum Setup Time (Local)
type: PropertyValue
value reference: Ease of Use

Free Cloud Tier Limit
type: PropertyValue
value reference: Pricing

Built-in Testing Framework
type: PropertyValue
value reference: Features

Setup Time (Baseline)
type: PropertyValue
value reference: Ease of Use

Infrastructure Flexibility
type: PropertyValue
value reference: Deployment

Native ML Features Count
type: PropertyValue
value reference: ML Capabilities

Commercial Support Tier
type: PropertyValue
value reference: Support

License Cost
type: PropertyValue
value reference: Pricing

DAG Creation Method
type: PropertyValue
value reference: Developer Experience

Typical Enterprise Deployment Time
type: PropertyValue
value reference: Time to Production