Oracle to Amazon Aurora PostgreSQL Migration: Approaches, Pitfalls, and Cost Savings

Moving away from Oracle is seldom just a matter of the database itself.

There is often existing application code in enterprises that have used Oracle for years and which may involve thousands of tables, crucial PL/SQL, integration, reporting workloads, and other custom code written around Oracle specifics.

This is why companies considering how to migrate Oracle to PostgreSQL must begin by figuring out the specifics of their current environment first.

While Amazon Aurora PostgreSQL could be used as a target for your migration, it cannot be done without doing much more than simply copying your data. Schema migration, application compatibility, testing, performance, cutover strategy, and cost analysis must all come into play.

Here is a practical way to approach the migration.

The first step in how to migrate Oracle to PostgreSQL is understanding the Oracle workload before selecting the migration method.

A useful assessment should identify:

This assessment tells you whether the workload is a relatively straightforward conversion or whether application and database refactoring will be required.

If you are still deciding whether the estate warrants moving at all, our modernization readiness assessment and the CIO’s guide to replatforming cover that earlier question.

There is no single migration pattern that works for every Oracle environment.

Two AWS tools commonly play an important role in the process: AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS).

AWS SCT analyzes Oracle database objects and converts supported schema elements and code for PostgreSQL. AWS DMS handles data movement and can support ongoing replication from the source during migration.

A simplified workflow looks like this:

The important distinction is that DMS is not a complete Oracle-to-PostgreSQL conversion engine.

That is why treating AWS DMS Oracle to Aurora as a “push-button migration” can create problems later. Teams new to the platform often pair this with an AWS consulting partner; the broader benefits of the AWS cloud set the context.

One of the biggest technical differences is the database programming language.

Oracle uses PL/SQL, while PostgreSQL uses PL/pgSQL. Similar business logic may need changes in syntax, functions, exception handling, data types, and database-specific behavior.

AWS SCT can automate significant portions of this conversion, but its output still needs technical review. AWS documentation specifically highlights differences in PL/SQL and PL/pgSQL and recommends resolving conversion warnings and errors before proceeding.

Application code can also require modification.

For example, applications may contain:

AWS guidance notes that applications using Oracle-specific interfaces may require code changes as part of the migration.

These details are exactly why a technical migration assessment matters. Structured QA is what turns that assessment into evidence before cutover.

Oracle to PostgreSQL migration cost is not simply the price of running the new database.

A realistic business case should compare:

Potential savings can come from reducing Oracle licensing expenses, infrastructure administration, and some operational overhead. However, migration itself introduces costs for assessment, conversion, application remediation, testing, engineering, and temporary parallel environments.

Aurora pricing is based on factors including database instances, storage, and selected configuration options. AWS also provides different pricing models and optimization options depending on workload characteristics. On the operational side, how DevOps reduces cloud infrastructure costs covers the running-cost half of the equation.

So, how much can an organization save?

A proper Oracle to PostgreSQL migration cost model should therefore use the organization’s actual workload rather than a generic “X% cheaper” claim.

For many workloads, PostgreSQL can be a viable alternative to Oracle. But that does not mean every Oracle workload should automatically move to PostgreSQL.

The right comparison depends on application requirements, database features, performance expectations, operational needs, compliance requirements, and the amount of Oracle-specific functionality embedded in the environment.

The question should be:

That is a much more useful question than comparing database brands in isolation. For the broader version of this call across an estate, see our modernize, rebuild or retire decision framework.

There is no reliable timeline based only on database size.

A relatively simple database with limited application dependencies may move in a shorter project window. A large enterprise environment with extensive PL/SQL, multiple applications, strict uptime requirements, and complex integrations can require several migration waves.

The major timeline drivers are:

At Impressico Business Solutions, we recommend establishing the timeline after assessment rather than promising a fixed duration before the workload is understood.

That is the same discipline agile and DevOps bring to legacy modernization.

A practical enterprise migration can follow this sequence:

During validation, teams should compare data, application behavior, queries, transactions, integrations, and performance.

AWS DMS can support ongoing replication so that source and target databases can remain synchronized during the migration process.

The final cutover should be treated as an operational event, with monitoring and rollback procedures already defined.

Common tools include:

Third-party migration and assessment tools may also be useful depending on the environment, but the toolset should follow the migration requirements rather than determine them.

At Impressico Business Solutions, we treat an Oracle to Aurora PostgreSQL migration as an application-and-database transformation process and not just moving the data.

This kind of process may involve database discovery, compatibility analysis, schema conversion, data migration, application adaptation, performance testing, cutover planning, and even optimization after migration. It sits within our wider application modernization on AWS practice, alongside legacy data warehouse modernization for the reporting and ETL workloads that usually travel with an Oracle estate.

Those reporting workloads have their own decisions attached — data lakes versus data warehouses and Kafka in modern data pipelines are where they usually land.

All in all, the main goal is very simple – to cut dependence on Oracle and to provide the company with a database that will help it proceed with growth.

When companies consider migrating Oracle to PostgreSQL, the first thing to do is not selecting a tool but understanding the requirements.

Impressico Business Solutions — legacy modernization, database migration and application modernization on AWS for enterprises reducing Oracle dependency.