ssis-migration

To migrate SSIS packages to Databricks, provide your DTSX files or stored procedures to generate Databricks notebooks following the Bronze/Silver/Gold Medallion pattern. This analysis extracts connections, control flow, and data flow components to build scalable pipelines.

The Medallion architecture is a data design pattern that organizes data into Bronze, Silver, and Gold layers. During SSIS migration, it maps stored procedures and DTSX components into structured Databricks notebooks for auditable, layered transformations.

Yes, you can migrate SSIS stored procedures to Spark notebooks by analyzing SQL patterns like INSERT, MERGE, and SCD. The process maps audit logic and transformations into equivalent Databricks notebook code.

Yes, the Databricks migration supports Unity Catalog integration and secure credential management. Generated notebooks include JDBC/Delta Lake references and utilize dbutils.secrets to safely handle connections and sensitive data.

Extracting connection managers, variables, and precedence constraints from DTSX files is handled automatically during package analysis. The process parses the XML structure to map these SSIS elements into Databricks notebook logic.

Migrating SSIS control flow to Databricks requires parsing DTSX components and mapping them to Spark logic. Complex custom scripts or unsupported native SSIS transforms may need manual adjustment after the automated notebook generation.