For PostgreSQL users, pgAdmin has long been the standard choice for managing databases. As teams work with more databases, they often need a tool with more features, such as DBeaver Enterprise.
As database teams grow and evolve, they face increasing challenges around collaboration and resource management. DBeaver Enterprise Edition and DBeaver Team Edition offer two distinct approaches to these challenges.
DBeaver PRO 25.2 is here, packed with updates to make working with your data faster and more enjoyable. With features like AI speech recognition and smarter data mapping, this new version helps you accomplish more with less effort.
When teams evaluate database tools, they’ll find two distinct approaches. Some platforms emphasize structured workflows and strict governance controls for database changes. Others focus on flexibility so teams can explore and collaborate with data the way they actually work.
DBeaver Enterprise and SQL Server Management Studio (SSMS) are trusted tools used by database professionals worldwide. Thanks to its reliability and native integration, SSMS is often the default choice for teams working with Microsoft SQL Server.
New York, NY, July 03, 2025 – DBeaver Corporation, a leading provider of universal database management tools, announced the release of DBeaver PRO 25.1 with new AI capabilities. The new AI features deliver intelligent assistance directly within the DBeaver interface, enabling users to write better queries faster, understand complex SQL instantly, and resolve errors with automated fixes.
Working with databases just got faster and smarter. You can now get instant help with queries, fix errors in seconds, and understand complex SQL at a glance. DBeaver 25.1 brings AI features that feel like a natural extension of your work, helping you stay in flow and solve problems more effectively. Here’s what’s new.
If your team works with data, chances are you’ve felt the growing need for better collaboration. Shared queries, centralized access, and consistent workflows can save hours if you have the right tool.
Real-world data rarely arrives clean or centralized. For many IT data analysts, it’s scattered across CSVs, Excel files, local folders, and cloud storage, and often from multiple sources.
Before analysis begins, analysts lose time importing files into a database, fixing formats, and aligning everything. It’s a slow, frustrating start to what should be a fast, insights-driven process.
