How to Migrate from Oracle to Amazon Aurora PostgreSQL

Many organizations are rethinking their reliance on Oracle. High licensing costs, vendor lock-in, and complex management make it harder to justify in a cloud-first world.

Amazon Aurora PostgreSQL has become a leading alternative. It combines PostgreSQL’s flexibility with AWS’s scalability and managed infrastructure, offering lower costs and enterprise-grade reliability.

But here’s the challenge: migrating from Oracle to Aurora PostgreSQL isn’t as simple as running an export and import. Oracle’s proprietary features (like PL/SQL), data type differences, and the need for minimal downtime make the process tricky. Traditional methods often involve long migration windows, operational risks, or duplicate pipelines.

This guide shows how Estuary Flow simplifies the process with real-time CDC and backfill pipelines, enabling a seamless, near-zero downtime migration path from Oracle to Aurora PostgreSQL. 

Oracle vs. Aurora PostgreSQL

Migrating from Oracle to Aurora PostgreSQL means shifting from a costly, proprietary system to a cloud-native, open-source–compatible database.

• Cost: Oracle requires expensive licenses, while Aurora uses pay-as-you-go pricing with no vendor lock-in.
• Architecture: Oracle relies on complex setups like RAC; Aurora automatically replicates across AWS zones with fast failover.
• Features: Oracle’s PL/SQL and proprietary types may need refactoring. Aurora offers standard PostgreSQL features and extensions.
• Scalability: Oracle scales vertically, Aurora scales horizontally with read replicas and elastic storage.

Bottom line: Aurora PostgreSQL reduces cost and complexity, but you’ll need to plan around Oracle-specific features.

Common Migration Challenges

Even though Aurora PostgreSQL is a strong alternative, moving from Oracle isn’t a copy-paste job. Here are the main hurdles:

• Schema & Data Types: Oracle’s NUMBER, CLOB, and BLOB need to be mapped to PostgreSQL equivalents (NUMERIC, TEXT, BYTEA). Mismatches can break queries if not handled correctly.
• PL/SQL Code: Oracle’s stored procedures, triggers, and packages don’t run natively on PostgreSQL. They must be refactored into PL/pgSQL or redesigned.
• Partitioning & Indexing: Advanced Oracle partitioning strategies may not translate 1:1, requiring re-architecture.
• Data Volume: Large backfills can take hours or days if done with batch tools. Without CDC, cutover usually means long downtime.
• Downtime Risk: Mission-critical apps can’t afford hours of outage. Continuous replication is essential to keep Oracle and Aurora in sync during migration.

The main challenge isn’t moving the data once, but keeping both systems aligned until cutover with minimal downtime.

Traditional Approaches (and Their Limitations)

Organizations have been migrating from Oracle to PostgreSQL for years, and AWS itself offers tooling to support this. However, traditional approaches often fall short when enterprises demand speed, accuracy, and minimal downtime.

1. AWS Schema Conversion Tool (SCT) + AWS Database Migration Service (DMS)

This is the most common AWS-native path:

• SCT: Converts Oracle schemas, stored procedures, and objects into PostgreSQL format.
• DMS: Handles the data migration, with options for full load and ongoing replication.

Limitations:

• Schema conversion is rarely seamless — complex PL/SQL often requires extensive manual rework.
• DMS change data capture (CDC) works, but it can be brittle, resource-heavy, and limited in how it handles schema changes.
• For very large datasets, full loads are slow, and ongoing replication can lag significantly under high write volumes.
• Debugging DMS failures often requires AWS support tickets and specialized expertise.

2. Manual Dump and Restore

Some teams choose to migrate by exporting Oracle data into flat files (CSV or SQL dumps) and importing into PostgreSQL.

• Works fine for small datasets or non-critical apps.
• Lets teams control the schema mapping and load order.

Limitations:

• Not realistic for production-scale databases.
• Requires downtime windows that can range from hours to days.
• No built-in CDC — meaning changes made in Oracle during migration are lost.

3. Custom ETL or Middleware

Engineering teams sometimes build pipelines using ETL tools or custom scripts to extract from Oracle and load into PostgreSQL.

• Offers flexibility in handling specific business logic.
• Can be integrated with existing ETL platforms.

Limitations:

• Expensive and time-consuming to build and maintain.
• Rarely supports true real-time sync — often works in batch mode.
• Breaks easily when schemas evolve or new tables are added.

4. Third-Party Migration Tools

Vendors like Quest SharePlex or Attunity (now part of Qlik) provide Oracle-to-Postgres replication.

• Mature tools with strong Oracle support.
• Some offer near real-time replication.

Limitations:

• Licensing can be expensive, reducing cost savings of leaving Oracle.
• Adds another vendor relationship to manage.
• May not integrate smoothly with AWS-native infrastructure.

Why These Approaches Fall Short

All of the above methods can get data from Oracle into PostgreSQL. But they share three common problems:

1. Downtime risk: Most approaches rely on batch transfers or replication tools that lag during cutover.
2. Complexity: Schema differences and PL/SQL refactoring still require heavy manual work.
3. Fragility: Traditional CDC pipelines struggle with schema evolution, large volumes, and ongoing reliability.

This is why enterprises exploring Oracle to Aurora PostgreSQL migrations are increasingly turning to real-time CDC platforms like Estuary Flow.

Before we walk through the Estuary setup, there are a few Oracle-specific prerequisites to make sure CDC will work properly.

Oracle CDC Prerequisites

Before connecting Oracle to Estuary Flow, make sure your database is prepared for CDC:

• Enable Archive Logs: Oracle’s redo logs must be archived so Estuary can read change events. Set a retention window (for example 7 days) long enough to recover from interruptions.
• Create a Dedicated User: Create a read-only user for Estuary (requires CREATE SESSION and SELECT permissions). For container databases, prefix the username with c##.
• Grant LogMiner Access: The user needs LOGMINING, SELECT_CATALOG_ROLE, and related privileges to read changes from redo logs.
• Create a Watermarks Table: Add a small helper table (for example FLOW_WATERMARKS) so Estuary can track its position in the stream.
• Enable Supplemental Logging: Run ALTER DATABASE ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS; to ensure all changes are captured.

Estuary supports Oracle versions 11g and newer, including both container and non-container databases.

Step-by-Step Tutorial: Migrate Oracle to Amazon Aurora PostgreSQL

Migrating from Oracle to Amazon Aurora PostgreSQL with Estuary Flow requires only a few guided steps. You do not need to write code or manage replication manually. Here’s how it works.

Step 1: Configure the Oracle Source Connector

• In the Estuary Flow web app, click + New Capture and choose Oracle Database (Real-time) as the connector.
  
  

  
  
  
• Enter your Oracle connection details:
  • Server Address (host:port)
  • Database (SID or PDB name, for example ORCL)
  • User and Password for a read-only user with LogMiner permissions
    
    

    
    
    
• (Optional) Toggle History Mode if you want to capture raw change events.
• Save and publish your capture.

Flow will backfill your existing Oracle tables into collections and then begin capturing real-time changes with CDC.

Watch the Demo: If you’d like to see Oracle CDC setup in action, here’s a quick demo using Estuary Flow. It walks through enabling archive logs, creating the Estuary user, and setting up Oracle for change data capture before connecting to Flow.

Step 2: Set Up the Aurora PostgreSQL Materialization

• Go to + New Materialization and select Amazon Aurora for Postgres as the destination connector.
  
  

  
  
  
• Provide the connection details:
  
  • Address: Aurora endpoint (host:port)
  • Database: Aurora logical database (for example postgres)
  • User and Password with table creation privileges
  • Schema: Defaults to public, but can be customized
    
    

    
    
    
• (Optional) Enable Delta Updates for efficient row-level updates or Hard Delete if deletes in Oracle should also remove rows in Aurora.

Step 3: Bind the Source to the Destination

• Under Source Collections, link the Oracle capture you created in Step 1.
• Assign each collection to a target table in Aurora. Estuary auto-creates the tables and keeps them updated.
• Click Publish to deploy your pipeline.

Once deployed, Estuary Flow continuously syncs Oracle with Aurora PostgreSQL in real time. Historical data is backfilled first, followed by ongoing CDC updates, ensuring you can cut over with minimal downtime.

You can monitor pipeline activity, review logs, and adjust sync behavior directly in the Estuary UI.

Result: You have a fully automated, real-time migration pipeline from Oracle to Amazon Aurora PostgreSQL without writing a single line of code.

Ready to build your pipeline now? Start for free. Stuck on a setting? Join our Slack

Why Estuary Flow is Different

Migrating from Oracle to Aurora PostgreSQL can be done with AWS-native tools like SCT and DMS, but these often create downtime, complexity, or maintenance overhead. Estuary Flow is built to solve those challenges with a modern approach.

1. Backfill + CDC in One Unified Pipeline

Estuary handles both historical data loads and ongoing CDC streams in a single pipeline. This eliminates the need to stitch together multiple tools, reducing complexity and risk.

2. Real-Time, Near-Zero Downtime Migration

Oracle changes stream into Aurora continuously. When you are ready to cut over, only a brief pause is needed for Flow to sync the final transactions, keeping downtime close to zero.

3. Exactly-Once Guarantees

Flow uses transactional semantics to ensure every event is delivered once and only once, even during failures or restarts. This provides stronger consistency than many traditional replication tools.

4. Flexible Schema Handling

Estuary enforces JSON-based schemas that automatically map into Aurora PostgreSQL tables. Schema evolution is supported, so changes in Oracle don’t break the pipeline.

5. Enterprise-Grade Security and Compliance

• Private deployments: Run Estuary Flow in your own cloud (BYOC) or private VPC for maximum control.
• Secure networking: Supports SSH tunneling, PrivateLink, and VPC peering to connect securely to databases.
• Compliance: Estuary is designed for regulated industries, with encryption in transit and at rest, audit trails, and fine-grained access controls.
• Data residency: You can configure Flow to use your own cloud storage buckets for compliance requirements.

6. No Code, No Infrastructure Overhead

Everything is configured through the Estuary. You don’t need to write scripts, manage servers, or patch middleware. Pipelines are fully managed or can be deployed privately with the same experience.

Key takeaway: Estuary Flow is not just faster and easier than SCT or DMS, it is also secure, compliant, and enterprise-ready. This makes it a safer choice for organizations migrating sensitive workloads from Oracle to Aurora PostgreSQL.

Need private deployment or strict compliance? Talk to us

Cost and Operational Benefits

Moving from Oracle to Amazon Aurora PostgreSQL with Estuary Flow delivers significant cost and operational advantages.

1. Lower Licensing and Infrastructure Costs

• Oracle: Licensing is tied to CPU cores and feature sets, often reaching six or seven figures annually. Additional features like partitioning, RAC, or spatial extensions add more fees.
• Aurora PostgreSQL: Pay only for the compute, storage, and I/O you use. There are no per-core or feature-based licensing costs. Scaling is elastic and predictable.

2. Reduced Migration Effort

• Traditional methods: Require multiple tools (SCT + DMS), manual schema rewrites, and downtime windows.
• Estuary Flow: A single pipeline handles backfill and CDC together. Less engineering effort means lower labor cost and faster time to value.

3. Operational Efficiency

• With Oracle, teams often manage complex clusters, backups, and monitoring.
• Aurora PostgreSQL is fully managed by AWS with automatic replication, patching, and failover.
• Estuary Flow removes the need to build or maintain replication middleware, reducing the ongoing burden on DBAs and data engineers.

4. Compliance Without Added Cost

• Oracle environments often require expensive add-ons for auditing, encryption, or secure networking.
• Estuary Flow provides built-in encryption, audit trails, and private deployment options. Compliance is achieved without costly extras.

5. Predictable Total Cost of Ownership (TCO)

By combining Aurora’s consumption-based pricing with Estuary’s unified pipelines, enterprises typically see:

• Good reduction in annual database costs compared to Oracle licensing.
• Faster migration projects that reduce consulting or engineering spend.
• Lower ongoing overhead because pipelines run continuously without manual babysitting.

Key takeaway: Oracle to Aurora PostgreSQL migration with Estuary Flow is not just a technical upgrade, it is a business cost transformation. Enterprises save on licensing, reduce migration timelines, and simplify long-term operations while staying compliant.

Want a tailored TCO estimate? Talk to us

Conclusion

Migrating from Oracle to Amazon Aurora PostgreSQL is a strategic move for organizations that want to cut costs, escape vendor lock-in, and modernize their data infrastructure. The challenge has always been how to do it safely, with minimal downtime, and without overwhelming engineering teams.

Traditional approaches like AWS DMS or manual dump-and-restore can work, but they often introduce risk, complexity, and extended cutover windows.

Estuary Flow changes the equation. By combining historical backfill and real-time CDC into one pipeline, Flow enables a seamless migration path where Oracle and Aurora stay perfectly in sync until you are ready to switch over. Add in enterprise-grade security, schema handling, and a no-code experience, and you have a solution designed for both speed and reliability.

If your organization is planning to move from Oracle to Aurora PostgreSQL, Estuary Flow offers the most efficient, compliant, and low-risk way to get there.

👉 Next step: Get started with Estuary Flow and try building your first Oracle to Aurora PostgreSQL pipeline today.