Compare
Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | Miller | DuckDB | act |
|---|---|---|---|
| Platforms | Universal, MCP, Claude Code, Codex, Cursor | Universal | GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | BSD-2-Clause | MIT | MIT |
| Stars | 10049 | 42451 | 72437 |
| Last activity | October 21, 2026 | September 28, 2026 | — |
| Install complexity | EASY | سهل — حزمة Python أو ملف CLI تنفيذي واحد | — |
| Category | Workflow, Data | Database | Testing, Git, DevOps |
| Best use | 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. | 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. | Best for a developer or small team that repeatedly edits GitHub Actions workflows and wants to test a job before pushing. It provides a local run log, while a final GitHub check remains necessary. It is not suitable when exact hosted-runner parity is required. |