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databricks-migration

Migrate Databricks notebooks, jobs, and Unity Catalog structures to Microsoft Fabric.

Updated Aug 19, 2026
Search Tags:#migration#databricks#Unity Catalog#onelake#microsoft fabric#notebookutils#dbutils
One-click install
npx skills add https://github.com/paulasilvatech/Fabric-Agentic-SDLC --skill databricks-migration-paulasilvatech
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-migration
Source: https://github.com/paulasilvatech/Fabric-Agentic-SDLC/tree/main/.github/skills/databricks-migration
Command: npx skills add https://github.com/paulasilvatech/Fabric-Agentic-SDLC --skill databricks-migration-paulasilvatech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Porting Databricks workloads to Microsoft Fabric requires replacing every dbutils call, collapsing Unity Catalog three-level namespaces, and re-platforming jobs, clusters, and MLflow tracking, which is error-prone without an exhaustive mapping reference. ## Core Features & Use Cases - Complete dbutils to notebookutils Mapping: Covers fs operations, secret scope to Key Vault URL conversion, notebook run/exit, widget replacement with parameter-tagged cells, and library install replacement with Fabric Environments. - Catalog and Storage Migration: Reduces Unity Catalog catalog.schema.table namespaces to Lakehouse schema.table structures and converts DBFS paths to OneLake abfss paths. - Workload Re-platforming: Maps Databricks Jobs to Spark Job Definitions, Delta Live Tables to notebooks plus Data Pipelines, Photon to Native Execution Engine, and MLflow tracking to Fabric ML Experiments. - Use Case: A data engineer inherits 50 Databricks notebooks using dbutils.secrets, widgets, and Unity Catalog tables, and needs each one rewritten for Fabric with correct notebookutils calls, parameter cells, and two-level schema references. ## Quick Start Migrate this Databricks notebook to Microsoft Fabric by replacing all dbutils calls with notebookutils and converting Unity Catalog table references to Lakehouse schemas.

Frequently Asked Questions about databricks-migration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I replace dbutils with notebookutils in Microsoft Fabric?▼

Most dbutils.fs methods like ls, cp, rm, and mkdirs are direct replacements in notebookutils.fs with OneLake paths instead of DBFS. Secrets map from dbutils.secrets.get(scope, key) to notebookutils.credentials.getSecret(keyVaultUrl, secretName), and notebook run/exit calls swap directly.

How to migrate Databricks widgets to Fabric notebooks?▼

Databricks widgets have no direct Fabric equivalent. Mark a cell as a parameters cell in the notebook UI, then override its default values via Pipeline Base parameters or notebookutils.notebook.run arguments. Use notebookutils.variableLibrary for centralized cross-notebook configuration.

Does Microsoft Fabric support Unity Catalog three-level namespaces?▼

Fabric Lakehouse uses a two-level namespace (schema.table) instead of Unity Catalog's catalog.schema.table. Migration strategies include one Lakehouse per catalog, one per schema, or medallion-aligned Lakehouses for bronze, silver, and gold layers.

Can I use dbutils.library.install in Fabric notebooks?▼

Runtime library installation via dbutils.library.install is not available in Fabric. Use Fabric Environments for reproducible, versioned library management, or %pip install plus notebookutils.session.restartPython() for ad-hoc session-scoped installs.

What is the Fabric equivalent of Databricks Photon?▼

Fabric Native Execution Engine (NEE) is the Photon equivalent, providing vectorized execution on Delta Lake. Enable it in workspace Spark settings or via %%configure with spark.microsoft.delta.nativeExecutionEngine.enabled set to true.

Why do Delta Live Tables pipelines fail when ported to Fabric?▼

Delta Live Tables have no Fabric equivalent, so verbatim ports fail. Rewrite DLT datasets as parameterized notebook cells orchestrated by Fabric Data Pipelines, mapping task dependencies to pipeline activity dependencies.

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