The hard part is the target model, not the copy
Moving rows between two databases is a solved problem. What sinks Oracle migrations is deciding how each type, sequence, and constraint should look on PostgreSQL, and discovering six months in that a decision was wrong. Conversion Studio makes those decisions explicit, reviewable, and repeatable before anything executes.
Four stages, each reviewable
Nothing touches the target until you have approved the model it will create.
Analyse the Oracle source
Read the source schema, discover tables and relationships, count rows, and convert what is there into a canonical model that migration planning works against.
Draft the PostgreSQL target
Generate a proposed PostgreSQL schema from the canonical model, then review it as a target model, a field mapping table, an ER diagram, and the actual DDL that would run.
Override what is wrong
Rename fields, change logical types, ignore columns, force JSON fallback, or split nested structures into child tables. Re-preview until the generated schema is what you actually want.
Run and validate
Execute the load with live progress, written and rejected record counts, and inspectable rejected samples. Each target entity is validated after the run rather than assumed correct.
What is automated, and what is not
Oracle is a fully supported migration source and PostgreSQL a fully supported target, but this path has characteristics worth planning around. We would rather set expectations here than during your cutover weekend.
| Aspect | Status on this path |
|---|---|
| Source schema discovery | Automated. Oracle has a dedicated schema reader and source modelling adapter. |
| Target schema generation | Automated. PostgreSQL has a dedicated draft generator and schema script generator. |
| Type mapping | Automated, with review recommended. Oracle sources use Oracle-specific mapping logic rather than the test-covered matrix that governs MySQL, MariaDB, PostgreSQL, and SQL Server conversions. |
| Change data capture | Reading Oracle's change stream depends on LogMiner and supplemental logging, which your DBA enables on the database. Without that, plan the move as a one-time full load with a cutover window. |
| Data load and validation | Automated. Batched writes with per-entity validation and rejected-record samples after the run. |
| PL/SQL packages, procedures, triggers | Not converted automatically. Procedural code needs rewriting for PostgreSQL, and Migratrix does not claim to translate it. |
| Application query changes | Not automated, but the risk assessment service can index your repositories and show which code touches the objects you are changing. |
Migration is the beginning, not the end
During a phased migration both systems often run in parallel. Schema and data comparison between PostgreSQL environments confirms the new estate matches what you intended as changes continue to land.
The PostgreSQL estate inherits the same promotion flows, approval gates, rollback generation, and audit trail, so the migration does not hand you a well-designed database with no change process around it.
Scheduled drift monitoring snapshots the new schema and reports what changed against a baseline, which matters most in the months after a migration when everyone is still adjusting things.