Migrate from Prefect to Mage Pro

Many teams start with Prefect for workflow orchestration—but soon encounter challenges with data engineering workflows, visual debugging, and developer productivity. Mage Pro offers a modern alternative: visual pipelines, built-in data integration, AI-assisted development, and UI-based deployment management—all within a unified platform for your data workflows.

Why migrate from Prefect to Mage Pro?

Prefect is a powerful orchestration tool, but it wasn’t designed for:

• Visual pipeline development and debugging
• Native data integration (ETL/ELT workflows)
• Mixing SQL and Python naturally in the same pipeline
• Streaming or event-driven data processing
• Built-in data previews and interactive development
• AI-powered pipeline development

Mage Pro is built to solve these challenges out-of-the-box, combining orchestration with data engineering capabilities in a modern, developer-friendly platform.

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Mage Pro vs Prefect: Benefits Overview

Mage Pro goes far beyond orchestration. It’s a unified platform for data integration, SQL modeling (native dbt blocks and Mage SQL blocks), AI-powered transformation, and streaming pipelines — all within a collaborative, Git-native workspace with UI-based deployment management.

Capability	Prefect	Mage Pro
Visual pipeline UI	⚠️ Code-only (Python decorators)	✅ Hybrid UI: drag-and-drop DAG builder + notebook-style coding experience
Built-in lineage	⚠️ Requires external tools	✅ Native, auto-generated data lineage
AI assistance	❌	✅ Generate, optimize, fix, and explain code with AI Sidekick
Multi-language support	⚠️ Python only	✅ SQL, Python, R, streaming, APIs
Data integration pipelines	⚠️ Custom Python or 3rd-party tools	✅ 200+ native connectors for databases, files, APIs
SQL block support	⚠️ Requires custom tasks	✅ Native dbt blocks, or Mage SQL block, preview, and test support
Incremental modeling	❌ (requires custom logic)	✅ Native in SQL block config and Data integration pipeline
Data previews & interactive runs	❌	✅ Preview data at every step, run blocks independently
Environment isolation	⚠️ Requires separate deployments	✅ Per-workspace configs, secrets, variables
Git integration	⚠️ Manual sync	✅ Git-backed version control and CI/CD, UI based Deployment App
Scheduling & triggers	✅ Cron + event triggers	✅ Cron, events, file triggers, webhooks, API
Secrets management	⚠️ Requires Prefect Cloud or external Vault	✅ Support both built-in secret manager, or external secret manager
RBAC & SSO	⚠️ Prefect Cloud only	✅ Built-in, enterprise-ready
Observability & logging	✅ Prefect Cloud UI	✅ Native UI for logs, metrics, traces, lineage
Scalability	⚠️ Manual worker configuration	✅ Auto-scaled executors on K8s or Docker
Streaming support	❌	✅ Kafka, CDC, real-time ingestion
Team collaboration	⚠️ Limited multi-tenancy	✅ Workspaces, permissions, activity logs

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Step-by-Step Migration Instructions

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Mapping Prefect Concepts to Mage Pro

Flows → Pipelines

Prefect:

from prefect import flow, task

@flow(name="my-etl-flow")
def my_etl_flow():
    data = extract_data()
    transformed = transform_data(data)
    load_data(transformed)

Mage Pro:

• Create a new pipeline in the UI
• Add blocks visually or via code
• Dependencies are defined by connecting blocks in the UI

Tasks → Blocks

Prefect:

@task
def extract_data():
    return pd.read_csv("data.csv")

@task
def transform_data(df):
    return df.dropna()

@task
def load_data(df):
    df.to_sql("table", engine)

Mage Pro:

• extract_data → Data loader block (Python or connector)
• transform_data → Transformer block (Python, SQL, or dbt block)
• load_data → Data exporter block (Python or connector)

Prefect Blocks → Mage Blocks

Prefect Block Type	Mage Pro Equivalent
S3Block, GCSBlock	Data loader/exporter blocks with native S3/GCS connectors
PostgresBlock, SnowflakeBlock	Data loader/exporter blocks with database connectors
DockerBlock, KubernetesJob	Executor configuration in pipeline settings

Scheduling & Deployments

Prefect:

from prefect import serve
from prefect.schedules import CronSchedule

@flow
def scheduled_flow():
    ...

if __name__ == "__main__":
    scheduled_flow.serve(
        cron=CronSchedule(cron="0 0 * * *")
    )

Mage Pro:

• Create a schedule trigger in the pipeline UI
• Configure cron expression, interval, or event-based triggers
• Use the Deployment App to manage deployments across environments (dev, staging, prod)
• No complex deployment setup needed—triggers and deployments are configured via UI

Secrets & Configuration

Prefect:

from prefect.blocks.system import Secret

@task
def use_secret():
    api_key = Secret.load("my-api-key")

Mage Pro:

• Use workspace variables or pipeline variables
• Access via variables dictionary in blocks
• Built-in secret manager with encryption, or integrate with external secret managers (AWS Secrets Manager, HashiCorp Vault, etc.)
• Secrets are isolated per workspace and pipeline

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Convert Prefect Flows with AI Sidekick

Skip the manual rewrites — Mage Pro’s AI Sidekick can automatically convert your Prefect flow code into a Mage pipeline with just one prompt.

How to Use It

1. Click the “Ask AI” button in the top-right corner of the Mage Pro UI.
2. Paste your Prefect flow code — including @flow, @task, or flow-based workflows.
3. Ask: “Convert this Prefect flow to a Mage pipeline.”
4. Sidekick will:
   • Parse the flow structure and task relationships
   • Generate the corresponding Mage blocks (data loader, transformer, data exporter)
   • Define block dependencies and scheduling logic
   • Convert Prefect blocks to Mage connectors where applicable
   • Optimize the generated code for performance and best practices
5. Review and insert the generated pipeline directly into your project.

Why Use Sidekick?

• Faster migration: turn entire flows into Mage pipelines in seconds
• Less error-prone: Sidekick understands scheduling, dependencies, and task types
• Code optimization: automatically optimizes generated code for performance
• Context-aware: uses your project setup and prior block structure
• Fully editable: review, tweak, and insert blocks before saving

👉 Learn more in the AI Sidekick docs.

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Tips for Migrating Complex Flows

Handling Prefect Subflows

Prefect:

@flow
def parent_flow():
    result = subflow()

@flow
def subflow():
    ...

Mage Pro:

• Split into separate pipelines and trigger them via API or use dynamic blocks for conditional logic
• Use block groups to organize related blocks within a pipeline

Prefect Task Runners & Concurrency

Prefect:

from prefect.task_runners import ConcurrentTaskRunner

@flow(task_runner=ConcurrentTaskRunner())
def parallel_flow():
    ...

Mage Pro:

• Configure concurrency settings in pipeline configuration
• Blocks with no dependencies run in parallel automatically
• Use executor configuration for custom parallelism on Kubernetes or Docker

Prefect Retries & Error Handling

Prefect:

@task(retries=3, retry_delay_seconds=60)
def risky_task():
    ...

Mage Pro:

• Configure retry settings in block or pipeline configuration
• Set retry count, delay, and backoff strategy
• Built-in error handling and alerting

Prefect Caching

Prefect:

@task(cache_key_fn=task_input_hash, cache_expiration=timedelta(hours=1))
def cached_task():
    ...

Mage Pro:

• Use block output caching in pipeline settings
• Configure cache expiration and invalidation rules
• Preview cached outputs in the UI

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After Migration: What You Get with Mage Pro

• Unified data platform: orchestration + data integration + transformation + streaming in one tool
• Visual pipeline builder with real-time data previews
• AI-powered block generation, optimization, and debugging (via AI Sidekick)
• Git-backed version control and CI/CD with UI-based Deployment App
• Built-in access controls, audit logs, and workspace isolation
• Support for SQL, Python, R, streaming, dbt blocks, Delta Lake, Iceberg, and more
• 200+ native connectors for databases, APIs, and cloud storage
• Streaming pipelines for real-time data processing
• Flexible secrets management: built-in secret manager or integrate with external systems (AWS Secrets Manager, Vault, etc.)
• Auto-scaled executors on Kubernetes or Docker
• Transparent pricing: usage-based pricing (SaaS) or cluster/workspace license-based pricing (self-hosted)

Prefect excels at orchestration. But when you need data engineering, visual development, and AI assistance — Mage Pro is built for modern data teams.

👉 Migrate to Mage Pro Today