DBCrust

High-performance database CLI for developers
Multi-database support • SSH tunneling • Vault integration • Advanced ORM analysis

[PyPI : pypi.org] [GitHub : github.com] [MIT License : opensource.org] [Rust 2024 : blog.rust-lang.org]

🚀 Why DBCrust?¶

A modern database CLI that speaks your language. DBCrust combines the speed of Rust with intelligent features like context-aware autocompletion, SSH tunneling, Vault integration, and powerful Django ORM analysis. Whether you're debugging production issues, analyzing data, or optimizing applications, DBCrust provides an unmatched developer experience.

✨ Core Features¶

SELECT id, na[TAB] → name, email, created_at
FROM us[TAB] → users, user_sessions, user_preferences
WHERE st[TAB] → status, state, start_date

dbc pos[TAB] → postgres://
dbc mo[TAB] → mongodb://
dbc docker://my[TAB] → docker://my-postgres-container
dbc session://prod[TAB] → session://production_db

○ Execution Time: 1.23 ms • Planning Time: 0.15 ms
Index Scan
│ Optimized lookup using email_idx
│ ○ Duration: 0.96 ms • Cost: 4 • Rows: 1
│   on users using email_idx
│   filter (email = 'user@example.com')
└► id • name • email • created_at

# Automatic tunnel detection
dbcrust postgres://user@db.internal.company.com/prod
# → Automatically routes through configured jumphost

# Dynamic credentials from Vault
dbcrust vault://app-role@database/postgres-prod
# → Fetches credentials automatically

# Interactive container selection
dbcrust docker://
# → 1. postgres-dev (postgres:15)
#   2. mysql-test (mysql:8.0)
#   3. redis-cache (redis:7)

# Direct container access with autocompletion
dbcrust docker://post[TAB] → docker://postgres-dev

# Save connections for easy reuse
\ss production_db

# Connect to saved sessions
dbcrust session://production_db

from dbcrust.django import analyzer

with analyzer.analyze() as analysis:
    # Your Django code
    books = Book.objects.all()
    for book in books:
        print(f"{book.title} by {book.author.name}")  # N+1 detected!

results = analysis.get_results()
print(results.optimization_suggestions)

🚨 N+1 Query Detected (CRITICAL):
  Query: SELECT * FROM books_book
  Followed by: 25x SELECT * FROM authors_author WHERE id = ?

💡 Fix: books = Book.objects.select_related('author').all()
Performance: 156ms → 12ms (92% improvement)

# Connect using Django database settings
python manage.py dbcrust

# Analyze specific Django database
python manage.py dbcrust --database analytics

-- Familiar SQL syntax that translates to MongoDB
SELECT * FROM users WHERE name LIKE 'John%' AND age > 18;

-- Advanced filtering with SQL operators
SELECT * FROM orders WHERE status IN ('pending', 'shipped')
  AND total BETWEEN 100 AND 1000;

-- Database management with SQL commands
CREATE DATABASE analytics;
CREATE COLLECTION user_events;

🏃‍♂️ Quick Start¶

curl -fsSL https://clement-tourriere.github.io/dbcrust/install.sh | sh

irm https://clement-tourriere.github.io/dbcrust/install.ps1 | iex

dbcrust postgres://user:pass@localhost/mydb
dbc postgres://user:pass@localhost/mydb  # Short alias

# Install as a tool (recommended for CLI usage)
uv tool install dbcrust

# Run immediately without installation
uvx dbcrust postgres://user:pass@localhost/mydb

# Add to Python project
uv add dbcrust
pip install dbcrust  # traditional pip

git clone https://github.com/clement-tourriere/dbcrust.git
cd dbcrust
cargo install --path .
dbcrust --help

🎯 First Connection¶

# PostgreSQL
dbcrust postgres://user:pass@localhost/myapp

# MySQL
dbcrust mysql://root:pass@localhost:3306/myapp

# SQLite
dbcrust sqlite:///./myapp.db

# ClickHouse
dbcrust clickhouse://user:pass@localhost:8123/myapp

# MongoDB
dbcrust mongodb://user:pass@localhost:27017/myapp
dbcrust mongodb+srv://user:pass@cluster.mongodb.net/myapp

# Docker containers (with auto-discovery)
dbcrust docker://my-postgres-container
dbcrust docker://my-mongo-container
dbcrust docker://   # Interactive selection

# Saved sessions
dbcrust session://production_db

🐍 Django Quick Start¶

For Django developers, DBCrust provides specialized ORM analysis tools:

# Install in your Django project
pip install dbcrust

# Connect using Django settings
cd your_django_project/
python manage.py dbcrust

# Test N+1 detection
python manage.py shell

# In Django shell
from dbcrust.django import analyzer

with analyzer.analyze() as analysis:
    for post in Post.objects.all():
        print(post.author.name)  # N+1 detected!

print(analysis.get_results().summary)

📖 Complete Django Setup Guide →

🎯 Real-World Examples¶

Database Administration¶

-- List all databases
\l

-- Show table sizes
SELECT schemaname,
       tablename,
       pg_size_pretty(pg_total_relation_size(schemaname || '.' || tablename)) as size
FROM pg_tables
WHERE schemaname = 'public'
ORDER BY pg_total_relation_size(schemaname||'.'||tablename) DESC;

Performance Analysis¶

-- Toggle EXPLAIN mode
\e

-- Now all queries show execution plans
SELECT u.email, COUNT(o.id) as order_count
FROM users u
         LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at > '2024-01-01'
GROUP BY u.email
HAVING COUNT(o.id) > 5;

DevOps Workflows¶

# Production database health check
dbcrust vault://readonly@prod/postgres-main \
  --query "SELECT version(), current_database(), current_user"

# Backup verification
dbcrust postgres://backup-user@replica.db.internal/app \
  --ssh-tunnel jumphost.company.com \
  --query "SELECT MAX(created_at) FROM critical_table"

🎨 What Makes DBCrust Special?¶

Modern CLI Experience¶

• Syntax highlighting for SQL and output
• History search with fuzzy matching
• External editor support for complex queries
• Session management with saved sessions and connection history
• Smart URL schemes with docker://, session://, recent://, vault://
• Shell autocompletion for connection URLs and contextual suggestions

Intelligent Features¶

• Named queries with parameter substitution
• Automatic paging for large result sets
• Copy-paste friendly output formats
• Error highlighting with helpful suggestions

Built for Speed¶

• Rust performance - start in milliseconds
• Efficient rendering - handle millions of rows
• Smart caching - autocompletion data persists
• Minimal memory footprint

🛡️ Security First¶

• ✅ TLS/SSL encryption by default
• ✅ SSH key authentication support
• ✅ Password-free workflows via Vault
• ✅ No plaintext storage of credentials
• ✅ Audit logging for compliance

🌟 Community & Support¶

Built with ❤️ using Rust, SQLx, and reedline

🤖 Proudly crafted with Claude Code — where AI meets thoughtful development.