dqex

🚀 One Tool. Every Environment. Even the Air-Gapped Ones.

dqex is a cross-platform database workbench that ships as a single static binary — no JVM, no Electron, no installers, no network required. It packs export, import, migration, comparison, snapshots, Excel data dictionaries, a full SQL terminal, and an AI assistant into one tool, with both a polished Web UI and a scriptable CLI.

• 🪶 Zero-dependency — copy it to a USB stick and run it on a bank's air-gapped server
• ⚡ Starts in <1s, ~50–60 MB memory footprint
• 🤖 AI-native agent — explores your real schema, writes dialect-correct SQL, and never executes without your confirmation
• 🧩 Web + CLI, one engine — same connections, saved tasks, and history on both sides
• 🌐 MySQL · PostgreSQL · Oracle with automatic dialect conversion for cross-type migration
• 📋 Excel data dictionaries & snapshot diff reports — compliance-ready by design (等保 / GDPR / audits)
• 🏠 Take production data home safely — conditional export + gzip, restore to your local test env in 2 commands

✨ Feature Highlights

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🧑‍💻 Quick Start

Download

Grab the zip for your platform from the Releases page and unzip — no installation required.

Linux / macOS

./install.sh                    # install to /usr/local/bin (optional)
dqex                            # start Web UI at 127.0.0.1:8181
# or run without installing:
./start.sh                      # foreground (Ctrl+C to stop)
./start.sh -d                   # background daemon
./stop.sh                       # stop the daemon

Windows

install.bat                     :: install to %LOCALAPPDATA%\dqex and add to PATH
dqex                            :: start Web UI in a new terminal
:: or run without installing:
start.bat                       :: foreground
start.bat -d                    :: background
stop.bat                        :: stop background service

CLI in 30 seconds

# Save a connection once, reuse everywhere
dqex conn add --name prod --type mysql --host 10.20.16.170 --port 3317 --un root --pw 'xxx'

# Export with conditions & gzip → take it home
dqex exp camunda -s prod -o backup.sql.gz --table-cond "orders:created_at >= '2026-01-01'"

# Restore to your local test database
dqex imp -t local_test -i backup.sql.gz --reset drop-and-create

# Interactive SQL terminal (native dialect, runs on the target DB)
dqex sql -c prod
dqex sql -c prod --json "SELECT id, name FROM users LIMIT 10"   # agent-friendly JSON

# Snapshot & compare — the killer feature for incident tracing
dqex snapshot create -c prod -n baseline
dqex snapshot compare -c prod --a baseline --b after-deploy

# Compliance: one command → styled Excel data dictionary
dqex dict camunda -s prod -o data_dict.xlsx

🤖 AI-Assisted SQL (Optional, Offline-Safe)

• Real schema, not guesses — the agent queries your actual table structures before generating SQL (Web UI shows live progress)
• Generate ≠ Execute — AI only produces SQL text; write operations require confirmation, dangerous statements are blocked, and you can \e-edit before running
• Full assist loop — \ai continue for follow-ups; Web UI supports generate / explain / optimize / fix with side-by-side diff preview and one-click apply
• Keys stay local — API key stored on your machine; only masked endpoint & model name are shown
• No config, no footprint — the AI entry only appears after BaseURL / API Key / Model are all configured; everything else keeps working untouched
• Offline fallback — built-in SQL template library (\template top_n orders amount 10) works in fully isolated networks

🛠️ Build from Source

make dev                # Go :8181 + Vite :5281 with hot reload & debugging
make build              # single binary ./dqex (frontend embedded)
make release            # cross-platform packages → release/
make install            # → /usr/local/bin

🧱 Tech Stack

• Backend: Go + infrakit (database dialect adaptation), Gin, embedded SQLite
• Frontend: React + TypeScript + Vite + Tailwind CSS + shadcn/ui + Monaco Editor
• Excel: excelize (pure Go, no CGO)
• Distribution: single static binary with embedded frontend, dark mode, i18n (EN/中文)

📚 Documentation

• CLI Manual — every command, flag, and meta-command
• Project Overview — philosophy, personas, and deep-dive scenarios
• Engineering Conventions — state modeling & data-flow rules (read before contributing)

🤝 Contributing

Contributions are what make open source great — and they earn you a place on the stargazers list too! ⭐

We welcome:

• 🐛 Bug fixes (highest priority)
• 📝 Documentation improvements (EN / 中文)
• 🧩 New SQL templates for the offline library
• 🗄️ Additional database driver support
• 🎨 UI/UX polish

How to contribute:

1. Fork the repo
2. Create a branch: git checkout -b feature/your-feature
3. Commit your changes: git commit -am 'feat: add something awesome'
4. Push: git push origin feature/your-feature
5. Open a Pull Request

Conventions: Go code follows gofmt; TypeScript follows ESLint + Prettier; commits follow Conventional Commits.

📄 License

MIT © 2026 fj1981

⭐ Star us on GitHub — it tells us you care, and helps more people discover the tool. Fork it, play with it, break it, and send us a PR!