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Migrating from Oracle to Amazon Aurora PostgreSQL can help organizations reduce licensing costs, move away from vendor lock-in, and adopt a more flexible cloud-native database platform. However, the migration process can become complex when large databases, Oracle-specific objects, or strict downtime requirements are involved.
The right approach depends on your database size, workload complexity, AWS environment, and how much downtime your business can tolerate. Below, we’ll look at the key migration challenges, available migration methods, and the general steps involved in moving an Oracle database to Aurora PostgreSQL.
Organizations migrate Oracle workloads to Aurora PostgreSQL for different reasons, but the most common ones are cost optimization, cloud modernization, and greater database flexibility.
Oracle is widely used for enterprise workloads, but licensing and infrastructure costs can become significant as environments grow. Aurora PostgreSQL, on the other hand, provides a managed PostgreSQL-compatible database environment within AWS.
Here is a simplified comparison:
| Area | Oracle | Amazon Aurora PostgreSQL |
|---|---|---|
| Licensing | Commercial database licensing | AWS consumption-based pricing |
| Database ecosystem | Proprietary | PostgreSQL-compatible |
| Infrastructure | Requires more direct administration | Fully managed AWS service |
| Scalability | Depends on architecture and infrastructure | Cloud-native storage and scaling capabilities |
| Migration compatibility | Oracle-specific features and PL/SQL | PostgreSQL standards with AWS integration |
For many organizations, the goal is not simply to replace one database with another. The migration is often part of a broader effort to modernize applications and move business-critical workloads to AWS.
However, Oracle and PostgreSQL are not identical platforms. Before migration, it is important to understand the technical differences that may affect schemas, application code, and the migration workflow.
Although both databases are relational platforms, migrating Oracle to Aurora PostgreSQL can involve more than exporting and importing data.
Oracle and PostgreSQL use different data types, syntax, and database objects. For example, Oracle NUMBER, CLOB, and BLOB fields may need to be mapped to compatible PostgreSQL data types.
Tables, indexes, constraints, sequences, and other schema objects should also be reviewed before migration. Incorrect mappings can lead to application errors or data consistency issues after cutover.
Oracle applications may rely heavily on PL/SQL packages, procedures, functions, and triggers. These objects cannot always be moved directly to PostgreSQL.
Some code may require conversion to PL/pgSQL or application-level refactoring. The amount of work depends on how extensively Oracle-specific functionality is used.
Migrating a large Oracle database can take significant time. If the database remains active while the initial migration is running, new transactions may continue to change the source data.
A one-time data export may therefore be insufficient for production systems. The migration process may also need a way to synchronize ongoing changes until the final cutover.
This is one of the most important challenges for online migrations.
After the initial data load, the Oracle database may continue receiving inserts, updates, and deletes. Those changes must be synchronized with Aurora PostgreSQL to ensure that the target database remains current.
This is where change data capture and continuous replication can become useful.
For business-critical applications, shutting down the Oracle database for a long migration window may not be acceptable.
A lower-downtime migration strategy usually involves:
The goal is to reduce the final interruption to the shortest practical window.
There is no single migration method that works for every Oracle environment. The best option depends on database size, application complexity, available expertise, and downtime requirements.
AWS Schema Conversion Tool (SCT) and AWS Database Migration Service (DMS) are commonly used for Oracle-to-Aurora migrations.
A typical workflow includes:
Schema assessment and conversion → Initial data migration → Ongoing replication → Validation → Cutover
AWS SCT can help assess and convert compatible database schemas, while AWS DMS can be used to migrate data and, depending on the configuration, replicate ongoing changes.
This approach can be suitable for organizations that already use AWS and have the technical resources to configure and manage the migration workflow.
However, Oracle-specific objects and complex PL/SQL code may still require manual conversion or additional testing.
For smaller or non-critical databases, a manual migration can be a simpler option.
The general process involves exporting data from Oracle, converting the schema to PostgreSQL-compatible syntax, importing the data into Aurora PostgreSQL, and validating the result.
This method may work well when:
For large production databases, however, a manual export/import process can create a long downtime window.
For large databases or business-critical workloads, continuous replication can provide a more controlled migration path.
Instead of moving the database in a single operation, the migration can be divided into several stages:
Initial Data Load → Ongoing Change Synchronization → Validation → Cutover
The existing data is migrated first. After that, new changes made to the Oracle database continue to be synchronized with Aurora PostgreSQL.
Once the target database has been validated and is sufficiently synchronized with the source, the application can be switched to Aurora PostgreSQL.
This approach is particularly useful when minimizing migration downtime is a priority.
The following workflow provides a general framework for planning and executing an Oracle-to-Aurora PostgreSQL migration.
The exact tools and configuration may vary depending on your environment, but the overall process is similar.
Start by evaluating the Oracle environment before moving any data.
Key areas to review include:
This assessment helps determine how much schema conversion and application refactoring may be required.
For large production databases, it is also important to estimate how long the initial data migration will take and whether ongoing synchronization will be required.
Next, create and configure the target Aurora PostgreSQL environment.
This typically includes preparing:
The Oracle source environment must also be able to communicate securely with the AWS target or the migration infrastructure being used.
Before starting the migration, confirm that the required ports, credentials, and network paths are available.
The next step is to convert the Oracle database schema into a format compatible with Aurora PostgreSQL.
This may involve converting or reviewing:
Automated schema conversion tools can help with compatible objects, but Oracle-specific functionality may still require manual adjustments.
It is generally better to test the converted schema in Aurora PostgreSQL before migrating the full production dataset.
Once the target schema is ready, you can begin transferring the existing Oracle data.
The migration method may include:
For smaller databases, the data transfer may be completed during a planned maintenance window.
For larger environments, the initial load may take longer. In that case, the source Oracle database may continue processing transactions while the historical data is being migrated.
For active production databases, new transactions may occur while the initial migration is running.
Without additional synchronization, the target database can quickly become outdated.
To address this, the migration workflow can use change data capture or continuous replication to synchronize ongoing:
The target Aurora PostgreSQL database can then continue catching up with the Oracle source until the final migration cutover.
This approach is especially important for organizations that need to reduce the amount of application downtime.
Before switching production workloads to Aurora PostgreSQL, validate both the database and the application.
Validation may include:
Testing should be performed before the final cutover whenever possible.
A migration should not be considered complete simply because the data transfer has finished. The target environment must also be able to support the application’s expected functionality and performance.
Once the Aurora PostgreSQL environment has been validated and synchronized, you can prepare for the final cutover.
A typical cutover process includes:
Pause or redirect application writes → Allow the target to catch up → Perform final validation → Update application connections → Monitor the new environment
The exact cutover procedure depends on the migration architecture.
For lower-downtime migrations, most of the data transfer and synchronization should already be complete before this stage. The final cutover should focus primarily on processing the remaining changes and switching the application to the new Aurora PostgreSQL database.
After the switch, monitor the new environment closely and verify application behavior.
For large Oracle databases and business-critical applications, reducing downtime is often one of the biggest migration challenges.
A one-time data migration can move historical data, but production systems may continue generating new transactions during the process. This makes it necessary to keep the source and target databases synchronized until the final cutover.
i2Stream provides a continuous migration approach that combines initial data synchronization with real-time or incremental replication. Historical data can be migrated first while ongoing changes continue to be synchronized to Aurora PostgreSQL, helping reduce the size of the final migration window.
For organizations planning a large-scale or low-downtime Oracle-to-Aurora PostgreSQL migration, i2Stream can provide an alternative approach to managing initial migration and ongoing synchronization in a unified workflow.
Can I migrate Oracle to Aurora PostgreSQL with minimal downtime?
Yes. A lower-downtime migration typically separates the process into an initial data migration, ongoing change synchronization, validation, and final cutover. By synchronizing changes before switching applications, the final migration window can be reduced.
What is the difference between AWS SCT and AWS DMS?
AWS SCT focuses primarily on assessing and converting database schemas and code where possible. AWS DMS is used for migrating and replicating data. In an Oracle-to-Aurora migration, both can be used as part of the overall migration workflow.
Do I need to convert Oracle PL/SQL to PostgreSQL?
In many cases, yes. Oracle PL/SQL procedures, packages, functions, and triggers may not be directly compatible with PostgreSQL and can require conversion or manual refactoring.
How do I migrate a large Oracle database to Aurora PostgreSQL?
Large databases can be migrated by first transferring historical data and then synchronizing ongoing changes until the target catches up. This approach can help avoid repeating the entire migration during the final cutover.
How do I validate an Oracle to Aurora PostgreSQL migration?
Validation can include row-count comparisons, data consistency checks, schema verification, application testing, query testing, and performance evaluation.
What is the best migration method for business-critical Oracle databases?
The best method depends on the environment and downtime requirements. For workloads that require a shorter cutover window, a migration approach that combines initial data loading with continuous synchronization can be more suitable than a single export/import operation.
Migrating Oracle to Amazon Aurora PostgreSQL typically involves four key stages: schema conversion, initial data migration, synchronization of ongoing changes, and final cutover.
The best migration method depends on factors such as database size, Oracle-specific functionality, application complexity, and acceptable downtime. Manual migration or AWS-native tools may be suitable for some workloads, while continuous synchronization can provide a more controlled approach for large or business-critical databases.
For organizations looking to simplify ongoing synchronization and reduce migration downtime, i2Stream provides an additional option for Oracle-to-Aurora PostgreSQL migration.
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