SoqlXplorer vs DBeaver Community Edition
Side-by-side comparison for macOS
SoqlXplorer
7.0Desktop client for Salesforce.com platform
DBeaver Community Edition
7.5Universal database tool and SQL client
| Metric | SoqlXplorer | DBeaver Community Edition |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| AI Score | 7.0 | 7.5 |
| 30-day Installs | 4 | 11.3K |
| 90-day Installs | 18 | 33.2K |
| 365-day Installs | 82 | 137.2K |
| Version | 4.6 | 26.0.4 |
| Auto-updates | Yes | Yes |
| Deprecated | No | No |
| GitHub Stars | — | — |
| GitHub Forks | — | — |
| Open Issues | — | — |
| License | — | — |
| Language | — | — |
| Last GitHub Commit | — | — |
| First Seen | Aug 9, 2023 | Aug 9, 2023 |
Reviews
SoqlXplorer
SoqlXplorer is a dedicated desktop client for interacting with Salesforce data, offering tools for running SOQL queries, schema visualization, and data export. It's a powerful tool for Salesforce developers and administrators seeking a robust environment for data management and analysis.
SoqlXplorer enables users to run and test SOQL queries, visualize Salesforce schemas, and export data efficiently.
Pros
- + Dedicated tool for Salesforce data management
- + Supports complex SOQL queries and schema visualization
- + Data export capabilities
- + Actively maintained
Cons
- - Limited to Salesforce users
- - Niche audience
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