antares vs dbdelve
Desktop database clients compared
antares and dbdelve are cross-platform desktop clients for connecting to databases and working with SQL. antares uses Electron and Vue with schema-management tools, while dbdelve is built with Rust and GPUI and supports a broader set of database engines and local file formats.
antares: Manage SQL Databases with a Desktop Client
Antares is a cross-platform SQL desktop client for developers who want database management and query editing in one workspace. It supports MySQL/MariaDB, PostgreSQL, SQLite, and Firebird, with releases for Windows, Linux, and macOS.
dbdelve: Native Cross-Platform Database Client in Rust and GPUI
DBDelve is a fast, lightweight, native database client built with Rust and GPUI for macOS, Linux, and Windows. It connects to multiple database engines and aims to offer a responsive alternative to heavier desktop clients.
| antares | dbdelve | |
|---|---|---|
| Language | Vue | Rust |
| License | MIT | GPL-3.0 |
| Stars | 2.7k | 628 |
| Forks | 173 | 37 |
| Last analyzed | Oct 3, 2026 | Oct 31, 2026 |
Key differences
- antares is built with Electron and Vue; dbdelve is built with Rust and GPUI.
- antares supports MySQL/MariaDB, PostgreSQL, SQLite, and Firebird; dbdelve lists those engines alongside Turso, DuckDB, Snowflake, SQL Server, MongoDB, Redis-compatible databases, and ClickHouse.
- antares includes tools for managing database objects such as indexes, views, triggers, and routines; dbdelve emphasizes editable results, reviewed data imports, query plans, and local-file queries.
- antares is licensed under MIT; dbdelve is licensed under GPL-3.0.
- Both projects describe themselves as under development. antares notes that it is in development, while dbdelve describes itself as being in its early days.
Choose antares if you…
- need a desktop client for MySQL/MariaDB, PostgreSQL, SQLite, or Firebird.
- want schema-management tools alongside query editing.
- prefer an MIT-licensed client with saved queries, notes, and todos.
Choose dbdelve if you…
- work with a wider range of database engines, including DuckDB, Snowflake, or SQL Server.
- want to query CSV, Excel, Parquet, or JSON files through in-memory DuckDB.
- need editable result grids, reviewed imports, or query-plan inspection.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.