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Studio 3T Community Edition vs DBeaver Community Edition

Side-by-side comparison for macOS

Studio 3T Community Edition

8.0
Developer Tools

IDE, client, and GUI for MongoDB

DBeaver Community Edition

7.5
Developer Tools

Universal database tool and SQL client

Metric Studio 3T Community Edition DBeaver Community Edition
Category Developer Tools Developer Tools
AI Score 8.0 7.5
30-day Installs 73 11.3K
90-day Installs 212 33.2K
365-day Installs 782 137.2K
Version 2025.1.0 26.0.4
Auto-updates Yes Yes
Deprecated No No
GitHub Stars
GitHub Forks
Open Issues
License
Language
Last GitHub Commit
First Seen Jul 25, 2025 Aug 9, 2023

Reviews

Studio 3T Community Edition

Studio 3T Community Edition is a free, open-source MongoDB IDE and GUI client that offers a comprehensive set of tools for database management and development. It supports features like query building, data visualization, and schema design, making it ideal for developers and data professionals working with MongoDB.

Studio 3T Community Edition provides tools for MongoDB development, management, and querying.

Pros

  • + Free and open-source community edition
  • + User-friendly interface for database management
  • + Comprehensive support for MongoDB features
  • + Cross-platform compatibility

Cons

  • - Community-driven updates may be less frequent
  • - Lacks some enterprise-level features

DBeaver Community Edition

DBeaver Community Edition is a versatile database tool supporting multiple database types, offering a user-friendly interface for SQL development and data management. It's ideal for developers, data analysts, and IT professionals who need a comprehensive database management solution.

Connects to various databases and provides tools for SQL development, data management, and database administration.

Pros

  • + Supports a wide range of databases
  • + User-friendly interface for SQL development
  • + Comprehensive set of tools for database management

Cons

  • - Lack of community discussion may indicate limited user engagement
  • - Potential performance issues with very large datasets