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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | Dagu | DuckDB | Miller |
|---|---|---|---|
| Platforms | Universal, MCP | Universal | Universal, MCP, Claude Code, Codex, Cursor |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | GPL-3.0 | MIT | BSD-2-Clause |
| Stars | 4491 | 42687 | 10051 |
| Last activity | October 28, 2026 | September 28, 2026 | October 21, 2026 |
| Install complexity | سهل للبداية؛ يحتاج ضبط أمان قبل المشاركة / Easy to start; security configuration required before sharing | سهل — حزمة Python أو ملف CLI تنفيذي واحد | EASY |
| Category | Workflow, DevOps, Monitoring | Database | Workflow, Data |
| Best use | Best for a developer or small team with connected scripts that need schedules, history, and a clear failure point. It adds dependencies, retries, and an operations UI without an external database in single-server mode. A simple independent command may not need it, and some team controls such as additional users, SSO, RBAC, and audit logging currently require a paid license. | Best for an analyst, developer, or small team that needs to inspect and join large data files and rerun analysis locally. It adds reviewable SQL without database-server setup. It is not a multi-user transactional database for many small concurrent writes from separate processes. | Ideal for developers, data analysts, and operators who need to clean a CSV export, inspect JSON Lines, or summarize a large file from the terminal without starting a Python project. Use it for quick, repeatable file processing; concurrent transactions and advanced visual analysis still call for a database or complementary analytics tool. |