Building a Pattern-Based Engine to Migrate ADF Pipelines from Synapse to Databricks
How we automated the migration of 500+ orchestration activities across 37 data factories — with zero manual JSON editing
Target audience: Data engineers migrating Azure cloud data platforms; technical architects evaluating ADF-to-Databricks strategies
Estimated read time: 12 minutes
The Problem
Your organization runs dozens of Azure Data Factory (ADF) factories containing hundreds of pipelines. Many of those pipelines read from or write to Azure Synapse Analytics (formerly SQL Data Warehouse) — and the decision has been made to migrate that workload to Databricks Unity Catalog.
A manual approach would require teams to open each pipeline in the ADF portal, replace activities, test, repeat. At 500+ impacted activities across 37 factories, that’s months of tedious, error-prone work.
We took a different approach: treat ADF pipeline JSON as a parseable AST, and build a compiler-like engine that rewrites it programmatically.
This post walks through the architecture, the key technical decisions, and the...
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