Oracle to PostgreSQL schema migration is one of the most common moves database teams make when trying to cut licensing costs without giving up a mature, transactional RDBMS. The two databases are both strict about data integrity, but they disagree on almost everything else — data types, sequence handling, procedural code, and naming conventions. Getting the schema right before you touch a single row of data is what separates a clean cutover from a multi-week firefight.
Why Teams Move From Oracle to PostgreSQL
Licensing is the usual trigger, but it's rarely the only reason. PostgreSQL has closed most of the feature gap with Oracle over the last decade — window functions, common table expressions, partitioning, and a genuinely extensible type system are all first-class. For most OLTP workloads, the migration is less about "can PostgreSQL do this" and more about "how do we map what we already built." That mapping starts at the schema level, not the data level.
Data Type Differences You'll Hit First
Oracle's NUMBER type is the first thing that trips people up — it's used for both integers and decimals, and a blanket mapping to numeric in PostgreSQL works but throws away precision hints that could have become integer or bigint. Other common mismatches:
VARCHAR2andCHARmap cleanly tovarcharandchar, but byte-vs-character semantics can differ for multi-byte encodingsDATEin Oracle always carries a time component; PostgreSQL'sdatedoes not, so many OracleDATEcolumns should actually becometimestampCLOBandBLOBboth map to PostgreSQL'stextandbytea, but large object handling at the driver level needs separate testing
None of this is exotic, but doing it by hand across a schema with hundreds of tables is where mistakes creep in.
Sequences, Identity Columns, and Auto-Increment
Oracle historically paired a SEQUENCE with a trigger to fake auto-increment behavior; newer Oracle versions support identity columns directly. PostgreSQL has native GENERATED ... AS IDENTITY syntax and standalone sequences, so both patterns have a home — but the migration tooling needs to recognize which pattern is in use and translate it, not just copy the sequence object and leave the trigger behind as dead code.
What Doesn't Translate Automatically
Tables, columns, indexes, and foreign keys translate reliably between dialects. Procedural code does not. PL/SQL packages, stored procedures, functions, and triggers are written in a language PostgreSQL doesn't speak — plpgsql is similar in spirit but different enough in syntax that automated translation is unreliable for anything non-trivial. Views usually translate, but ones that lean on Oracle-specific functions (DECODE, NVL, hierarchical CONNECT BY queries) need a manual rewrite. Flagging these for review up front — instead of discovering them mid-cutover — is the difference between a planned migration and an emergency one.
A Schema-First Migration Workflow
The workflow that holds up under pressure looks like this: connect to both the Oracle source and the PostgreSQL target, compare the two schemas, and generate the migration SQL needed to bring the target in line. This is the same approach that works for any dialect pair — see our guide on how to compare two database schemas and generate migration SQL, and the parallel walkthrough for MySQL to PostgreSQL migration. A readiness view that separates "translates cleanly" (tables, columns, keys, indexes) from "needs manual review" (views, functions, triggers) lets you scope the manual work honestly instead of guessing.
Reducing Risk During Cutover
Whatever tool generates the migration SQL, three habits keep the process safe: run it as a dry run first so you can read the exact statements before anything executes, take a schema snapshot immediately before applying changes so you have a rollback point, and use a skip-on-error mode for large batches so one failing statement doesn't block hundreds of others. These aren't Oracle-specific precautions — they're the same discipline we recommend for any cross-dialect move, including SQL Server to PostgreSQL migrations.
FoxSchema handles the Oracle-to-PostgreSQL comparison natively, including sequence and identity-column detection, and flags PL/SQL objects for manual review instead of silently dropping them. Read the documentation for the full dialect support matrix, or head to the download page to try it against your own schema — self-hosting it in Docker is covered on the self-hosting page if you'd rather run it on your own infrastructure.
