Database systems > Oracle Database 23ai vs. Amazon Aurora PostgreSQL 17 Compatible
Selecting a database involves evaluating factors such as data model, scalability, security, and integration with existing infrastructure. Oracle Database 23ai and Amazon Aurora PostgreSQL 17 Compatible represent distinct approaches to database management, each with its own strengths and weaknesses.
This comparison analyzes real-world performance, user feedback, and key differentiators to help you make an informed decision.
Quick Verdict
For organizations prioritizing AI integration, advanced security, and a converged database approach, Oracle Database 23ai is the stronger choice. If you are heavily invested in the AWS ecosystem and need a scalable, PostgreSQL-compatible database, Amazon Aurora PostgreSQL is well-suited.
- Oracle 23ai is a converged database with strong AI integration and advanced security features.
- Aurora PostgreSQL offers PostgreSQL compatibility, scalability, and tight integration with AWS services.
- Oracle's licensing model can be complex while Aurora's is usage-based.
Who Should Choose Which?
Choose Oracle Database 23ai if:
Enterprises requiring a converged database with built-in AI capabilities, advanced security features, and multi-cloud support, and are willing to invest in a more complex licensing model.
Choose Amazon Aurora PostgreSQL 17 Compatible if:
Organizations already heavily invested in AWS services, seeking a scalable, PostgreSQL-compatible database with a simpler, usage-based pricing model.
Key features – Side-by-Side
| Attribute | Oracle Database 23ai | Amazon Aurora PostgreSQL 17 Compatible |
|---|---|---|
| Database Model | Converged database (Relational, JSON, Spatial, Graph, Vector) | Relational (PostgreSQL compatible) |
| Scalability | Globally Distributed Database, automated shard rebalancing, True Cache | Scalable storage up to 128 TB, instance scaling, up to 15 read replicas, decoupled compute and storage |
| High Availability | RAC, Active Data Guard, Raft replication in Globally Distributed Database, Transparent Application Continuity | Automated backups, fast failover, Multi-AZ deployments, Aurora Global Database |
| Security Features | SQL Firewall, TLS 1.3, extended password length, column-level auditing, Data Dictionary Protection, AI-enhanced anomaly detection, OCI IAM, Microsoft Entra ID | SSL/TLS encryption, AWS IAM, Kerberos authentication, Amazon GuardDuty integration |
| Cloud Integration | Optimized for OCI, multi-cloud support (AWS, Azure, Google Cloud), OCI IAM, Microsoft Entra ID | Integrates with various AWS services (DMS, Glue, Redshift) |
| AI Capabilities | AI-enhanced query processing, AI Vector Search, AI-enhanced anomaly detection | Limited native AI capabilities |
Overall Comparison
Pros and Cons
Oracle Database 23ai
- Converged database approach with built-in AI
- Advanced security features like SQL Firewall
- High availability options such as RAC and Active Data Guard
- Strong in handling mission-critical workloads and complex data types
- Integrates AI directly into the database engine, enabling real-time AI-driven insights
- AI Vector Search allows for semantic information retrieval from unstructured data
- True Cache to speed up query response time and improve overall scalability
- Offers features to simplify management tasks
- Optimized for Oracle Cloud Infrastructure (OCI) and supports multi-cloud deployments
- Offers JSON Relational Duality, support for JavaScript, and a Multilingual Engine
- Provides Active Data Guard for disaster recovery and business continuity
- No major disadvantages reported.
Amazon Aurora PostgreSQL 17 Compatible
- Scalable storage up to 128 TB without manual intervention
- Supports instance scaling and read scaling
- Can scale reads using up to 15 low-latency read replicas
- Compute and storage are decoupled
- Automated backups
- Fast failover
- Multi-AZ deployments
- Aurora Global Database for multi-Region HA and DR
- Built-in security
- Supports SSL and TLS encryption
- Integration with AWS Identity and Access Management (IAM)
- Supports Kerberos authentication
- Integration with Amazon GuardDuty for threat detection
- Integrates with various AWS services
- Integrates with AWS Database Migration Service (DMS) and AWS Glue for data migration and ETL processes
- Can integrate with Amazon Redshift for data warehousing
- Compatible with PostgreSQL JDBC, ODBC, and PSQL drivers
- Supports multiple extensions to enhance database functionality
- Fully managed by AWS, handling backups, patching, scaling, and high availability
- Managed high availability (HA) and disaster recovery (DR) capabilities in and across AWS Regions
- Some consider it expensive compared to self-managed solutions
- Oracle Database offers enterprise-level features such as high availability, reliability, and ACID compliance
User Experiences and Feedback
Oracle Database 23ai
- No highlights reported.
- No major complaints reported.
- No value feedback reported.
Amazon Aurora PostgreSQL 17 Compatible
- Offers up to 3x the throughput of standard PostgreSQL
- Achieve up to 1.7 times higher write throughput and 1.38 times better price performance with Amazon Aurora PostgreSQL on AWS Graviton4-based R8g instances
- Gives developers exceptional control over data modeling and query behavior
- Reduces operational complexity through automated scaling, backups, and patching, targeting teams who prioritize simplicity over configurability
- Some consider it expensive compared to self-managed solutions
- Compared to Oracle Database 23ai in terms of scalability and high availability, Oracle Database offers enterprise-level features such as high availability, reliability, and ACID compliance
- Provides flexible, cost-effective pricing with notable performance benefits
Frequently Asked Questions
Which database offers better scalability?
Both offer excellent scalability, but Oracle's Globally Distributed Database provides horizontal scalability, while Aurora offers scalable storage and read replicas.
Which database is easier to manage?
Amazon Aurora PostgreSQL is fully managed by AWS, simplifying management tasks. Oracle requires more hands-on management, although it offers features to simplify administration.
Sources & Citations
- Official product specifications
- Expert reviews from tech publications
- User feedback from online forums
Information gathered through AI-assisted web search and analysis. Last updated: September 2025
Methodology & Transparency
Our comparison methodology combines multiple data sources to provide comprehensive, unbiased analysis:
- Data Collection: We gather information from official specifications, user reviews, and independent testing
- AI-Assisted Analysis: Advanced AI helps process large amounts of data while maintaining accuracy
- Human Oversight: All comparisons are reviewed for accuracy and relevance
- Regular Updates: Content is refreshed to reflect new information and user feedback
- Bias Mitigation: We strive for objectivity by considering multiple perspectives and sources
Versusly.ai uses AI-assisted content generation combined with human oversight to deliver comprehensive comparisons. We are transparent about our process and continuously work to improve accuracy and usefulness.