SSIS to Databricks Migration
Migrate SQL Server Integration Services packages to PySpark notebooks and Databricks Workflows without rewriting every mapping by hand. AI-assisted translation + deterministic parity tests = a migration you can trust.
Why SSIS to Databricks is hard
Control flow vs. Spark
SSIS is workflow-oriented; Spark is data-parallel. Re-architecting this by hand introduces subtle errors.
Package complexity
Script tasks, custom components, lookups and SCDs hide business rules that are rarely documented.
Manual rewrite risk
A 100-package estate can take 12–18 months and cost £1M+ in consultancy fees before it is production-ready.
Mapping SSIS concepts to Databricks
| SSIS concept | Databricks equivalent |
|---|---|
| Package | Databricks Notebook / Job |
| Control Flow | Workflow DAG |
| Data Flow | DataFrame transformations |
| OLE DB Source | JDBC/ODBC or Delta read |
| Derived Column | Spark SQL expression |
| Lookup | DataFrame join or broadcast |
| Slowly Changing Dimension | Delta Lake merge |
| Script Task | Python function |
How LogicLift migrates SSIS to Databricks
Ingest
Upload .dtsx packages, configurations and dependencies. LogicLift inventories every control flow, data flow and transformation.
Translate
Choose the deterministic compiler or agentic pipeline to convert SSIS logic into idiomatic PySpark, Spark SQL and Databricks Workflows.
Validate
Run synthetic and real-data parity tests to prove row-level equivalence before any cutover.
Deploy
Export production-ready notebooks, jobs and Airflow DAGs. Keep the old SSIS packages warm until you are confident.
What you get
- Production-ready PySpark notebooks and Databricks Jobs
- Row-level parity tests on synthetic and real data
- Human-in-the-loop review for regulatory sign-off
- 60–80% reduction in migration time vs. manual rewrite
- Complete audit trail and migration spec for compliance
Frequently asked questions
Can SSIS packages run in Databricks?
SSIS packages cannot run natively in Databricks. LogicLift translates the business logic inside those packages into PySpark and Spark SQL so the same transformations run on Databricks.
How long does an SSIS to Databricks migration take?
A manual rewrite typically takes 12–18 months for a 100-package estate. LogicLift reduces this to 6–10 weeks by automating the translation and parity testing.
What is the cost of migrating SSIS to Databricks?
Manual consultancy rates range from £150–£250 per hour, leading to six-figure bills. LogicLift charges a fixed platform fee and cuts migration effort by 60–80%.
Can you migrate SSIS to Azure Data Factory instead?
Yes. LogicLift can also target Azure Data Factory, Microsoft Fabric and dbt. Many teams choose Databricks for advanced analytics and Spark workloads.
Ready to move your SSIS estate to Databricks?
Book a free 30-minute migration assessment. We will review your package inventory and show you the fastest path to Databricks.