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 Django applications, DBCrust provides an unmatched developer experience.

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

Why DBCrust?

DBCrust is a high-performance database CLI built for modern developers. Beyond standard database management, it provides context-aware autocompletion, SSH tunneling, HashiCorp Vault integration, and Docker support. Built in Rust for speed, with specialized features for Django developers including real-time ORM analysis and N+1 query detection.

🚀 Key Features

• 🐳 Multi-Database & File Format Support - PostgreSQL, MySQL, SQLite, MongoDB, ClickHouse, Elasticsearch, plus Parquet, CSV, JSON files via Apache DataFusion
• ⚡ Intelligent CLI - Context-aware autocompletion, syntax highlighting, and external editor support
• 🔐 Enterprise Ready - SSH tunneling, HashiCorp Vault integration, and encrypted connections
• 🔍 Smart Performance Analysis - Built-in EXPLAIN visualization and query optimization tools
• 🐍 Django ORM Analyzer - Real-time N+1 query detection, performance monitoring, and optimization recommendations
• 📊 Python Library - Complete programmatic access with unified CLI and Python APIs

Quick Start

Installation

# Native install (fastest, recommended)
curl -fsSL https://clement-tourriere.github.io/dbcrust/install.sh | sh  # Unix
# irm https://clement-tourriere.github.io/dbcrust/install.ps1 | iex  # Windows

# Or via uv (Python package manager)
uvx dbcrust postgres://user:pass@localhost/mydb  # Run immediately
uv tool install dbcrust  # Install as isolated tool (recommended)

Basic Usage

# Multi-database connections with intelligent autocompletion
dbcrust postgres://user:pass@localhost/mydb   # PostgreSQL
dbcrust mysql://user:pass@localhost/mydb      # MySQL
dbcrust elasticsearch://localhost:9200        # Elasticsearch
dbcrust mongodb://localhost:27017/mydb        # MongoDB
dbcrust clickhouse://localhost:8123/default   # ClickHouse
dbcrust docker://postgres-container           # Container auto-discovery
dbcrust session://production_db               # Saved sessions

# File format connections (Parquet, CSV, JSON)
dbcrust parquet:///data/sales_2024.parquet    # Parquet files
dbcrust csv:///logs/*.csv?header=true         # CSV with glob patterns
dbcrust json:///api_responses.json            # JSON/NDJSON files

Essential Commands

# Multi-database connections
dbcrust postgres://postgres:pass@localhost/myapp     # PostgreSQL
dbcrust elasticsearch://localhost:9200               # Elasticsearch (no auth)
dbcrust mongodb://user:pass@localhost:27017/mydb     # MongoDB
dbcrust clickhouse://user:pass@localhost:8123/default # ClickHouse
dbcrust docker://my-postgres-container               # Container auto-discovery

# Interactive commands (once connected)
\dt                               # List tables
\d users                         # Describe table
\e                               # Toggle EXPLAIN mode
\cs                              # Column selection for wide results
\ss production_db                # Save current connection

Advanced Features

# EXPLAIN visualization - toggle with \e
SELECT * FROM users WHERE email = 'user@example.com';
# ○ Execution Time: 1.23 ms • Planning Time: 0.15 ms
# Index Scan using email_idx (Cost: 4, Rows: 1)

# SSH tunneling for secure connections
dbcrust postgres://user:pass@db.internal.com/myapp --ssh-tunnel jumphost.com

# HashiCorp Vault integration
dbcrust vault://app-role@database/postgres-prod

🐍 Django & Python Integration

Django ORM Performance Analysis

# Real-time ORM analysis with middleware (fastest setup)
# settings.py
MIDDLEWARE = ['dbcrust.django.PerformanceAnalysisMiddleware', ...]

# Or manual analysis
from dbcrust.django import analyzer
with analyzer.analyze() as analysis:
    books = Book.objects.all()
    for book in books:
        print(book.author.name)  # Detects N+1 automatically

results = analysis.get_results()  # Get optimization recommendations

Perfect for Django teams: N+1 detection, performance monitoring, CI/CD integration, and real-time optimization suggestions.

📖 Complete Django Integration Guide →

Python API

import dbcrust

# Direct command execution
result = dbcrust.run_command("postgres://user:pass@localhost/mydb", "SELECT * FROM users LIMIT 10")

# Launch interactive CLI from Python
dbcrust.run_cli("postgres://user:pass@localhost/mydb")

# PostgresClient class for object-oriented usage
from dbcrust import PostgresClient
client = PostgresClient(host="localhost", user="postgres", dbname="myapp")
tables = client.list_tables()

📖 Complete Python API Documentation →

Documentation & Support

• 📚 Complete Documentation - Installation, usage guides, and API reference
• 🔧 Command Reference - All 40+ interactive commands
• 🐍 Django Integration - ORM performance analysis
• 🐛 Issues & Support - Bug reports and questions
• 📦 PyPI Package - Python package information

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Built with ❤️ using Rust • Modern database CLI • Security-first architecture