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.

What I like best about EDB for PostgreSQL is how stable and dependable it has been for our production workloads. We use it for backend services and transactional operations, and performance has remained consistent even during higher traffic periods. The replication, backup, and monitoring capabilities reduced a lot of manual operational work for our team and made maintenance easier overall. I also liked that it keeps the flexibility of PostgreSQL while adding enterprise-level features that help with scalability, security, and administration. Another thing that stood out was the compatibility support during migration and deployment activities, which helped avoid unnecessary downtime and simplified the transition process for our developers and database team.

Query Profiler & Log Analysis: A specialized UI that visually breaks down slow-running queries and highlights bottlenecks, similar to Oracle’s AWR (Automatic Workload Repository) reports. Model Manager: A UI dedicated to managing external inference services (like OpenAI or local models), so users can swap models through a GUI instead of changing infrastructure code. Unified Billing & Activity Logs: A clean administrative dashboard that consolidates cloud infrastructure costs and database charges into a single view. The UI tools are clearly designed to look and feel familiar to Oracle users. For example, EDB’s Postgres Workload Reports are formatted almost identically to Oracle’s performance reports, which significantly reduces the learning curve for teams moving away from a legacy database. Onboarding is treated as a "Time to Value" exercise rather than just a software download. It typically follows a structured pat Case Management: How to use the EDB Support Portal and set up "Named Contacts." Lasso Tooling: Installation of EDB’s diagnostic tool, which collects system metadata to help support engineers troubleshoot your specific environment faster. Architecture Design: Defining the HA (High Availability) and DR (Disaster Recovery) strategy. Security Hardening: Implementing Row-Level Security and Transparent Data Encryption (TDE). "AI Intelligence" of EDB PostgreSQL . EDB focuses on three pillars: Sovereign AI (keeping data local), Vector Intelligence (native high-speed search), and Agentic Workflows (autonomous database agents).