TablePro vs DBeaver Community Edition
Side-by-side comparison for macOS
TablePro
8.0Native database client for many database types
DBeaver Community Edition
7.5Universal database tool and SQL client
| Metric | TablePro | DBeaver Community Edition |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 7.5 |
| 30-day Installs | 623 | 11.3K |
| 90-day Installs | 1.7K | 33.2K |
| 365-day Installs | 1.7K | 137.2K |
| Version | 0.38.0 | 26.0.4 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | 671 | — |
| GitHub Forks | 54 | — |
| Open Issues | 12 | — |
| License | AGPL-3.0 | — |
| Language | C | — |
| Last GitHub Commit | 1mo ago | — |
| First Seen | Mar 6, 2026 | Aug 9, 2023 |
Reviews
TablePro
TablePro is a modern, native database client for macOS supporting MySQL, PostgreSQL, SQLite, and MongoDB. It offers a built-in AI assistant and a sleek interface, making it ideal for developers and data professionals seeking a powerful yet user-friendly tool.
Provides a native database client for MySQL, PostgreSQL, SQLite, and MongoDB with an AI assistant.
Pros
- + Supports multiple database systems natively
- + Includes a built-in AI assistant for enhanced functionality
- + Open-source and free to use
Cons
- - Limited community traction and engagement
- - AGPL license may pose considerations for some users
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