PopSQL vs DBeaver Community Edition
Side-by-side comparison for macOS
PopSQL
8.0Collaborative SQL editor
DBeaver Community Edition
7.5Universal database tool and SQL client
| Metric | PopSQL | DBeaver Community Edition |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 8.0 | 7.5 |
| 30-day Installs | 264 | 11.3K |
| 90-day Installs | 832 | 33.2K |
| 365-day Installs | 3.0K | 137.2K |
| Version | 1.0.135 | 26.0.4 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | 7 | — |
| GitHub Forks | 2 | — |
| Open Issues | - | — |
| License | NOASSERTION | — |
| Language | PHP | — |
| Last GitHub Commit | 3mo ago | — |
| First Seen | May 19, 2017 | Aug 9, 2023 |
Reviews
PopSQL
PopSQL is a collaborative SQL editor designed for teams to work together on SQL queries in real-time. It offers features like real-time editing, version control integration, and support for multiple database types. It is ideal for developers and teams working on data projects.
PopSQL allows users to collaboratively edit SQL queries in real-time, providing a shared workspace for teams to work on database queries together.
Pros
- + Real-time collaborative editing for SQL queries
- + Integration with tools like dbt and support from Timescale
- + Useful for teams working on data projects
Cons
- - Limited community engagement and GitHub activity
- - Potential limitations in database support
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