> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mage.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Migrate from Airbyte to Mage Pro

Many teams start with Airbyte for data integration—but soon encounter challenges with flexibility, orchestration, and observability. Mage Pro offers a unified alternative: a single platform for data integration, transformation, and orchestration with **AI-assisted pipeline development** and **enterprise-ready scalability**.

## Why migrate from Airbyte to Mage Pro?

Airbyte is popular for ELT pipelines, but it wasn't designed for:

* Native orchestration of transformations
* Visual, modular pipeline building
* AI-powered debugging and code generation
* Git-native CI/CD and multi-environment deployments
* Streaming pipelines and event triggers

Mage Pro replaces Airbyte’s connector-based model with **end-to-end data integration pipelines** that seamlessly combine **extract, load, and transform steps**—all while giving teams full code flexibility and better observability.

***

## ✨ Mage Pro vs Airbyte: Benefits Overview

Mage Pro combines [**data integration**](/data-integrations/overview) and [**data orchestration**](/orchestration/triggers/triggering-pipelines) in a single, developer-friendly platform.

| Capability                     | Airbyte                                          | Mage Pro                                                   |
| ------------------------------ | ------------------------------------------------ | ---------------------------------------------------------- |
| **Data integration**           | ✅ Pre-built connectors                           | ✅ Native connectors for APIs, databases, files             |
| **Orchestration**              | ⚠️ Basic scheduling only                         | ✅ Full DAG-level orchestration                             |
| **Visual pipeline UI**         | ⚠️ Connector-based only                          | ✅ Drag-and-drop pipeline builder                           |
| **Custom transformations**     | ⚠️ Limited (requires dbt or custom code)         | ✅ Python, SQL, or AI-generated transformations             |
| **AI assistance**              | ❌                                                | ✅ Generate, debug, and optimize pipelines with AI Sidekick |
| **Incremental loads**          | ✅ Supported via config                           | ✅ Supported natively in pipeline settings                  |
| **Schema discovery & testing** | ⚠️ Limited                                       | ✅ Data previews, schema validation, tests                  |
| **Streaming & CDC**            | ⚠️ Limited                                       | ✅ Native support for Kafka, CDC, and real-time ingestion   |
| **Git integration**            | ⚠️ Manual export/import only                     | ✅ Git-backed pipelines and CI/CD                           |
| **Secrets management**         | ⚠️ Env-only                                      | ✅ Built-in secrets & workspace isolation                   |
| **Multi-environment support**  | ❌ Manual, not native                             | ✅ Dev, staging, and production workspaces                  |
| **Observability**              | ⚠️ Basic logs                                    | ✅ Detailed logs, lineage, and monitoring                   |
| **Scalability**                | ⚠️ Self-managed in OSS, limited control in Cloud | ✅ Auto-scaled executors on Kubernetes or ECS               |

***

## 🛠️ Step-by-Step Migration Instructions

<Steps>
  1. **Inventory your Airbyte connectors**
     * List all sources and destinations in your Airbyte setup
     * Note incremental or full-load settings
     * Export transformation logic (e.g., dbt, SQL scripts)

  2. **Create a Mage Pro workspace**
     * Sign up at [Mage Pro](https://cloud.mage.ai)
     * (Optional) Connect your Git repository for version control

  3. **Recreate connectors as Mage data integration blocks**
     * Each Airbyte source → **Extract block** in Mage
     * Each Airbyte destination → **Load block** in Mage
     * Any dbt or SQL logic → **SQL block** (dbt-like features built-in)
     * Use **Python blocks** for custom transformations

  4. **Configure pipelines**
     * Combine extract → transform → load in a single pipeline
     * Use the visual editor or YAML pipeline config

  5. **Set up scheduling and triggers**
     * Replace Airbyte sync schedules with Mage cron or event-based triggers
     * Optionally add webhooks or file-based triggers

  6. **Run and validate pipelines**
     * Preview data outputs at every step
     * Compare final tables and schema to ensure parity
     * Validate incremental load and deduplication logic

  7. **Monitor and optimize**
     * Use Mage’s built-in logs and data lineage
     * Configure alerts and retry rules
     * Leverage auto-scaling for parallel extracts and loads
</Steps>

***

## 🤖 Convert Airbyte Configs with AI Sidekick

Mage Pro’s **AI Sidekick** can automatically help convert Airbyte connector configurations and dbt logic into Mage pipelines.

### 🔧 How to Use It

1. Open your Mage Pro workspace and click **“Ask AI”**
2. Paste your Airbyte connector settings or dbt SQL models
3. Ask: **“Convert this Airbyte source-destination flow into a Mage pipeline.”**
4. Sidekick will:
   * Generate Extract/Load blocks for your sources and targets
   * Translate transformation steps into SQL or Python blocks
   * Create a complete pipeline with triggers and dependencies
5. Insert the generated pipeline directly into your workspace.

***

## 🧠 Tips for Migrating Complex Airbyte Flows

* Merge multiple Airbyte connectors into a **single end-to-end pipeline**
* Use **pipeline variables** for shared config (e.g., table names, batch sizes)
* Replace dbt transformations with **SQL blocks** (supports `ref()`, tests, and incremental models)
* For large tables, enable **batching and streaming modes**

***

## ✅ After Migration: What You Gain

* Unified **integration + transformation + orchestration**
* Visual pipelines and instant debugging
* AI-powered pipeline creation and troubleshooting
* Git-based CI/CD and environment isolation
* Real-time streaming support (Kafka, CDC, webhooks)
* Enterprise-grade RBAC, audit logs, and observability

> No more juggling Airbyte, Airflow, and dbt. With Mage Pro, you get a single platform for all data workflows.

👉 [Start Migrating to Mage Pro](https://cloud.mage.ai)