Oracle Database is one of the most capable relational engines ever built, and one of the most expensive to keep. Per-core licensing, a core factor applied to every eligible CPU, hard-partitioning rules that cap virtualization savings, mandatory support uplifts, and the ever-present risk of a license audit combine to make Oracle a perennial target for cost reduction. The good news is that the open-source and cloud-native database landscape has matured to the point where most Oracle workloads have a credible home. The catch is that “credible” depends heavily on how much Oracle-specific logic you have.
What determines your target
The single biggest factor is your PL/SQL and Oracle-feature surface area. A schema that is mostly tables, views, and portable SQL moves almost anywhere. Heavy use of packages, autonomous transactions, CONNECT BY, materialized-view refresh semantics, or RAC narrows your options and inflates the conversion effort. Assess this first, before you fall in love with a destination.
The three paths, compared
PostgreSQL is the default destination and the one most teams should evaluate first. It is a mature, standards-leaning, fully open database with an extension for almost everything, no license fee, and a deep tooling ecosystem (ora2pg does most of the mechanical conversion). Choose it when you want to eliminate licensing entirely and are willing to own the operational side or buy third-party support.
Amazon Aurora (PostgreSQL-compatible) suits teams that want out of Oracle and out of the database-operations business. You get managed backups, patching, and replicas, and AWS DMS plus the Schema Conversion Tool handle much of the lift. It is not free, it is usage-based, so model it against your steady-state load rather than assuming cloud automatically means cheaper.
MySQL fits simpler, read-heavy or web-tier workloads where you do not need PostgreSQL’s richer feature set. It is ubiquitous and easy to hire for, though its procedural language and datatype handling differ enough from Oracle to require careful conversion.
Whichever you pick, the work is schema and PL/SQL conversion, application-SQL changes, and rigorous parallel-run validation, not the data movement itself. Each path below opens to a full cost model, a phase-by-phase plan, and an in-depth guide.