FileMaker Pro vs DBeaver Community Edition
Side-by-side comparison for macOS
FileMaker Pro
7.5Relational database and rapid application development platform
DBeaver Community Edition
7.5Universal database tool and SQL client
| Metric | FileMaker Pro | DBeaver Community Edition |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 7.5 | 7.5 |
| 30-day Installs | - | 11.2K |
| 90-day Installs | 28 | 33.2K |
| 365-day Installs | 187 | 137.2K |
| Version | 22.0.6.601 | 26.0.4 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | — | — |
| GitHub Forks | — | — |
| Open Issues | — | — |
| License | — | — |
| Language | — | — |
| Last GitHub Commit | — | — |
| First Seen | Aug 21, 2020 | Aug 9, 2023 |
Reviews
FileMaker Pro
FileMaker Pro is a powerful relational database and rapid application development platform ideal for creating custom solutions. It offers user-friendly tools for building databases and applications, making it beneficial for small businesses and non-technical users seeking robust, scalable solutions.
It serves as a relational database and rapid application development platform.
Pros
- + User-friendly interface for database creation and app development
- + Quick application development capabilities
- + Strong integration with other tools and platforms
Cons
- - Steep learning curve for advanced features
- - Not free
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