Effortless migration from legacy data tools

The Challenge

Data teams often find themselves shackled by a fragmented and outdated toolkit. You might have one platform for basic data ingestion (like Fivetran or Airbyte), another complex system for orchestration (like Apache Airflow), and a separate environment for data modeling (like dbt Cloud). Each tool comes with its own learning curve, operational overhead, and limitations in flexibility, scalability, or observability. The thought of migrating from these entrenched systems can feel overwhelming—a "lift and shift" nightmare filled with manual rewrites, debugging headaches, and the constant fear of breaking critical production workflows. It’s like trying to move house with all your belongings still glued to the floor.

The Solution: Your Expert Migration Partner and Unifying Platform

Mage isn't just another data tool; it's a unified platform designed to simplify, accelerate, and de-risk your migration journey from legacy systems and fragmented tools. We offer comprehensive support, intelligent automation, and a consolidated environment that brings all your data engineering workflows under one roof.

Dedicated Migration Guides

We understand the nuances of popular data tools. Mage offers specific migration guides to help you transition from:

• Fivetran: Moving beyond "black-box" connectors to gain full control, custom transformations, and cost transparency.

• Apache Airflow: Overcoming scalability, debugging, and developer productivity challenges with visual pipelines, built-in observability, and AI assistance.

• Airbyte: Unifying data integration, transformation, and orchestration, addressing limitations in flexibility and visibility.

• dbt Cloud: Consolidating dbt's transformation power with Mage's orchestration, multi-language support, and auto-scaled execution.

• Estuary: Extending real-time data capture with robust transformation, orchestration, and better cost control. These guides provide clear, step-by-step instructions to ensure a seamless transition.

AI-Assisted Migration and Code Conversion

The AI Sidekick plays a pivotal role in accelerating your migration. It can assist in converting existing configurations and even entire workflows from tools like Airflow or Estuary into Mage pipelines. By understanding your project setup and block structure, the AI generates context-aware and fully editable code, drastically reducing the manual effort of rewriting.

Unified Platform Benefits

By migrating to Mage, you gain a platform that integrates data integration, transformation, and orchestration into a single, cohesive system. This means:

• Visual Pipelines: A drag-and-drop builder for end-to-end workflow visualization.

• Multi-Language Support: Combine SQL, Python, R, and even dbt models within the same pipeline.

• Enhanced Observability: Native UI for logs, metrics, and traces, eliminating the need for external monitoring tools.

• Automated Scalability: Auto-scaled execution on Kubernetes/ECS for efficient handling of concurrent jobs, without manual tuning.

• Robust CI/CD: Git-backed version control, integrated deployment workflows, and rollback capabilities for confident releases.

• Enterprise-Grade Security: RBAC, audit logs, and workspace isolation to meet stringent compliance requirements.

Expert Migration Support Plans

For larger or more complex migrations, Mage offers dedicated support plans (Essential, Extended, Complete). Our team can provide hands-on migration support for up to 10, 40, or even 100 pipelines from your existing Mage projects or legacy systems. This expert guidance minimizes downtime, optimizes performance, and ensures best practices are followed.

Real-World Scenario: Consolidating a Data Stack at a Growing Tech Company

Imagine a rapidly growing tech company that has accumulated a sprawling data stack. Their data engineers are constantly context-switching between Airbyte for ingestion, Airflow for orchestration, and dbt Cloud for transformations. This leads to slow development, inconsistent data, and a high operational burden.

To streamline their operations, they decide to migrate to Mage:

1. Phased Migration: They start by migrating their most critical data ingestion and transformation pipelines from Airbyte and dbt into Mage, utilizing the specific migration guides.

2. AI-Assisted Conversion: For complex Airflow DAGs, their engineers use the AI Sidekick to help convert Python operators into Mage blocks, accelerating the rewriting process and maintaining business logic.

3. Unified Orchestration: Once in Mage, they can visually combine these previously disparate ingestion, transformation (including dbt models), and custom Python/SQL logic into single, cohesive pipelines.

4. Benefits Realized:

   • Reduced Costs: Eliminating per-row fees and optimizing compute with Mage’s intelligent scaling.

   • Faster Development: Engineers spend less time on manual orchestration and more time building new features, aided by AI-powered code generation.

   • Improved Reliability: Centralized monitoring and built-in data validation catch issues proactively, while instant rollbacks provide a safety net for deployments.

   • Enhanced Collaboration: All data logic is in a single, version-controlled environment, fostering better teamwork and easier onboarding for new hires.

By migrating to Mage, the tech company transforms its data operations from a fragmented, high-effort landscape into a unified, efficient, and intelligent ecosystem, allowing them to scale their data initiatives with confidence and agility.