UI / UX: The interface is clean and easy to navigate, making routine database administration and monitoring straightforward.

Integrations: EDB integrates well with PostgreSQL tools and enterprise environments, making migration and deployment easier.

Performance: It delivers stable, reliable performance for production workloads with excellent scalability and high availability features.

Pricing / ROI: While the pricing is higher than community PostgreSQL, the enterprise features, security, and support provide good value for organisations with critical workloads.

Support / Onboarding: The support team is responsive and knowledgeable, and the documentation helps simplify deployment and ongoing management.

AI / Intelligence: AI capabilities are still evolving, but the platform offers useful monitoring, diagnostics, and performance optimisation features that help administrators manage databases more efficiently. Review collected by and hosted on G2.com.

The pricing can be a bit high for smaller organisations, and some advanced features have a learning curve for new users. The management interface could be more modern, and expanding AI-driven monitoring, automation, and optimisation capabilities would further improve the overall experience. Review collected by and hosted on G2.com.

What I like most about EDB for PostgreSQL is its enterprise-grade reliability, strong security features, and Oracle compatibility, which makes migrations simpler for organizations. It delivers excellent performance along with high availability, plus robust backup and disaster recovery capabilities. I also find the platform easy to manage, and it scales well for mission-critical workloads. On top of that, the technical support is responsive, which makes it a dependable choice for enterprise database environments. Review collected by and hosted on G2.com.

One area that could be improved is the licensing cost, which may be a consideration for smaller organizations. Some advanced features require additional configuration, and the initial setup and migration process can feel complex for teams without PostgreSQL expertise. More comprehensive documentation, along with clear step-by-step guides for advanced use cases, would also be helpful. Review collected by and hosted on G2.com.

EDB for PostgreSQL stands out because it takes the strengths of open‑source Postgres and adds the kind of enterprise features that large organizations rely on. You get high availability with near‑continuous uptime, advanced security like transparent data encryption and audit logging, and strong Oracle compatibility that makes migrations smoother. On top of that, it’s designed to run seamlessly across cloud, on‑premises, and hybrid environments, so teams don’t feel locked into one setup. In short, it’s the combination of reliability, security, and flexibility that makes EDB such a practical choice for mission‑critical workloads. Review collected by and hosted on G2.com.

One drawback of EDB for PostgreSQL is that it can feel more complex and costly compared to using community Postgres, especially when setting up advanced features like distributed clusters or Oracle compatibility. The licensing and support fees add up, and smaller teams may find the learning curve steeper than expected. Review collected by and hosted on G2.com.

What I like most about EDB for PostgreSQL is its enterprise-grade offering built for real-world design and manageability. I really value the enhanced tooling and support, and the robust tools for monitoring, management, and high availability, which are crucial for production environments. It has significantly reduced a lot of operational burden and helped optimize performance, especially as demand grows. I also appreciate EDB's dedication to contributing to and supporting the open source PostgreSQL project, which ensures the core technology keeps advancing. The monitoring dashboard has been valuable for me. In one case during a data validation task, I noticed slow queries affecting overall throughput, and I turned to the EDB monitoring dashboard to pinpoint which query and resources were involved. That let me identify complex join operations that needed more efficiency, and it guided me to optimize the queries directly, like adding a composite index or rewriting query logic. After using the monitoring dashboards to identify slow queries and implement targeted optimizations, we saw about a 30% improvement in average query execution time for critical queries, along with a noticeable decrease in overall database CPU load, especially during peak hours. The performance tuning tools were a great asset for optimization and helping with migration challenges around slow query execution and resources. Review collected by and hosted on G2.com.

The configuration is a bit complex for me. There are sometimes too many configuration options, and I'd like to see a more streamlined, simpler approach for common use cases, especially for initial setups and ongoing tuning. I also want to see better integration with newer workflows like AI and ML. When I tried integrating EDB with custom AI model pipelines, the main challenge was around data integration and transformation. The output format wasn't immediately ready for the AI model's input requirements, and the documentation around custom data connectors and advanced data shaping was a bit lacking. That led me to do a lot of manual scripting and debugging to bridge the gaps, and I spent extra time writing custom scripts to transform data between EDB and the AI model format instead of leveraging more streamlined EDB features. I'd have liked to see more examples, clearer documentation, standardized configurations, and more robust connectors and frameworks to handle this kind of processing directly. The data shaping for AI/ML is my top priority for improvement. On the documentation side, while the docs are good for fixed scenarios, some scenarios can sometimes be a bit dense, and I'd like more practical examples. Review collected by and hosted on G2.com.

I like EDB for PostgreSQL for running SQL queries, validating application data, and troubleshooting data-related issues efficiently. I also enjoy using EDB for PostgreSQL because it feels familiar when you have some experience with PostgreSQL and SQL. Tasks like running queries, checking data, and troubleshooting issues are very straightforward. Review collected by and hosted on G2.com.

I find the initial setup and configuration a little hard without prior PostgreSQL experience. I also feel monitoring and management could be improved for non-technical users initially. Additionally, I found that areas like user roles permissions, connectivity, and migrating existing SQL workloads required additional effort. Review collected by and hosted on G2.com.

I appreciate EDB for PostgreSQL for its stability, strong enterprise support, advanced replication and failover capabilities, performance-tuning features, and overall compatibility with PostgreSQL, all of which make it easier to manage production workloads. Review collected by and hosted on G2.com.

I haven’t run into any major issues so far. If anything, the main opportunities for improvement would be a more intuitive user experience, clearer and more complete documentation, and more automation to streamline routine administrative tasks. Review collected by and hosted on G2.com.

I like that EDB for PostgreSQL offers the reliability of open source PostgreSQL with enterprise-grade tooling and support. The compatibility with standard PostgreSQL is excellent, making migration and integration smooth. The additional management tools, like monitoring and tuning features, make life easier compared to plain PostgreSQL. The support team is responsive and knowledgeable, which is reassuring when dealing with production workloads. For scaling and compliance, EDB adds real value. Review collected by and hosted on G2.com.

The licensing costs can feel heavy compared to just using community PostgreSQL. Documentation can be more beginner-friendly in certain areas. Review collected by and hosted on G2.com.

What I like best about EDB is its enterprise grade PostgreSQL platform with strong performance, scalability, and reliability. The UI/UX is clean and easy to use, and the integrations with cloud and enterprise tools make deployment simpler. It also provides good ROI compared to traditional databases, along with excellent support and smooth onboarding. I especially appreciate the intelligent monitoring and automation features that help reduce manual database management effort. Review collected by and hosted on G2.com.

One area where EDB could improve is pricing, as some advanced enterprise features and support plans can become expensive for smaller teams. The UI/UX for certain administration and monitoring features also feels slightly complex at first and has a learning curve. Additionally, while integrations are strong, configuring advanced setups and performing performance tuning may require expertise in PostgreSQL. I’d also like to see more AI-driven insights and automation capabilities to simplify database optimization and troubleshooting further. Review collected by and hosted on G2.com.

What I like best about EDB for PostgreSQL is that it brings enterprise-level reliability and support to open-source PostgreSQL. It makes managing backups, monitoring, performance, and high availability much easier and more consistent.

The Oracle compatibility features are especially helpful for migrations, reducing the amount of rework needed. The tooling improves daily DBA workflows, and the support team adds confidence when handling production issues.

Overall, EDB delivers strong performance, useful integrations with the PostgreSQL ecosystem, and good ROI for teams running mission-critical databases. Review collected by and hosted on G2.com.

What I dislike about EDB for PostgreSQL is that it can feel complex to set up and manage, especially for teams without deep PostgreSQL expertise. Some advanced features require a learning curve, and onboarding could be more streamlined.

The UI and management tools are useful, but they could be more modern and intuitive. Pricing can also be a concern for smaller teams, since the best ROI is usually for larger or mission-critical environments.

I’d also like to see simpler integrations, clearer documentation for migrations, and more built-in AI or intelligent recommendations for tuning, monitoring, and troubleshooting. Review collected by and hosted on G2.com.

What I like most about EDB for PostgreSQL is its reliability and ease of managing enterprise-level databases. It provides the flexibility of PostgreSQL along with additional enterprise features that make database administration and monitoring easier. I also found it helpful for handling production workloads because of its stability and performance. Another good thing is the support and documentation, which are useful when troubleshooting issues or learning new features. Review collected by and hosted on G2.com.

One thing I dislike about EDB for PostgreSQL is that some features and configurations can feel a little complicated for new users. In the beginning, it may take time to understand all the tools and settings properly. Sometimes the interface and documentation can also feel too technical, especially for people who are not very experienced with PostgreSQL. I think the setup and learning process could be made simpler and more beginner-friendly. Review collected by and hosted on G2.com.