🚀 SQL Graph Visualizer v1.1.0 - PostgreSQL Support Implementation

This major feature release introduces comprehensive PostgreSQL support to the SQL Graph Visualizer, enabling seamless operation with both MySQL and PostgreSQL databases.

Key Features

Multi-Database Architecture

Generic DatabasePort Interface: Unified interface abstracting database operations
Repository Factory Pattern: Dynamic database repository selection
Full Backward Compatibility: All existing MySQL functionality preserved

PostgreSQL Integration

Complete Connectivity: Full PostgreSQL driver integration with connection pooling
Query Execution: Supports all SQL operations needed for data transformation
Configuration Support: Environment-based configuration with SSL options
Chinook Sample Database: Ready-to-use PostgreSQL setup with sample data

Technical Improvements

Refactored Transform Service: Updated to use generic database interface
Enhanced Configuration System: Support for database type selection via config
Docker Compose Setup: Complete PostgreSQL development environment
Validation Suite: Comprehensive testing and validation scripts

Quick Start

PostgreSQL Setup

# Start PostgreSQL with Chinook sample data
docker-compose -f docker-compose.postgresql.yml up -d

# Run application with PostgreSQL
CONFIG_PATH=config/config-postgresql-chinook.yml go run cmd/main.go

Validation

# Run comprehensive validation
./validate_postgresql_implementation.sh

Development

Essential Commands

# Build and run
make build && make run

# Run tests
make test

# Development setup
make dev

Impact

This implementation provides a solid foundation for multi-database support while maintaining the application's core functionality and performance characteristics. Users can now:

Choose Their Database: Work with either MySQL or PostgreSQL
Migrate Seamlessly: Switch between database types without code changes
Scale Flexibility: Use the best database for their specific use case
Maintain Performance: Enjoy consistent performance across both database types

Closes Issue #7: PostgreSQL Support Implementation
Pull Request #14: PostgreSQL Support Implementation - Issue #7

Full Changelog: v1.0.0...v1.1.0

SQL Graph Visualizer v1.0.0 - First Release

This is the first major release of SQL Graph Visualizer - a powerful Go application that transforms SQL database structures into Neo4j graph databases with interactive visualization capabilities.

What's New in v1.0.0

Core Features

Direct Database Connection (Issue #10)

Complete workflow from database connection to Neo4j transformation
Automatic schema discovery and analysis
Security validation with connection assessment
Production-ready performance (sub-100ms analysis)

Professional CLI Tool - `sql-graph-cli`

4 Main Commands: analyze, test, generate, config
Interactive experience with rich console output
Configuration management with YAML support
Built with Cobra framework for professional CLI experience

Intelligent Schema Analysis

Automatic table discovery and relationship detection
Junction table recognition for many-to-many relationships
Graph pattern detection (star schema, hub-and-spoke)
Foreign key relationship mapping
Data size estimation and performance optimization

Security & Validation

Connection security validation (SSL/TLS checks)
Permission analysis and read-only enforcement
Timeout controls and connection pooling
Security level rating (LOW/MEDIUM/HIGH)

Technical Specifications

Architecture

Domain Driven Design (DDD) with clean architecture
Layered structure (domain, application, infrastructure, interface)
Repository pattern with ports and adapters
Dependency injection and separation of concerns

Supported Technologies

Source Database: MySQL 8.0+ (PostgreSQL planned for v1.1.0)
Target Database: Neo4j 4.4+
Language: Go 1.24+
API Layer: GraphQL (gqlgen), REST (Gorilla Mux)
Configuration: YAML-based with Viper

Performance

Analysis Speed: Sub-100ms for typical databases
Memory Efficient: Configurable batch processing
Connection Pooling: Optimized for high throughput
Scalable: Handles datasets from small to enterprise-scale

Comprehensive Testing

Integration Tests

Real database validation with Sakila test database
Full workflow testing from connection to analysis
Performance benchmarking and validation
Error handling and edge case coverage

Test Results (Sakila Database)

16 tables analyzed successfully
16 transformation rules generated (14 nodes, 2 relationships)
4 graph patterns identified (star schema variants)
10,395 rows processed (~4.96 MB dataset)
Analysis completed in 50-60ms

Usage Examples

Quick Database Test

sql-graph-cli test --host localhost --port 3306 --username user --password pass --database mydb

Complete Schema Analysis

sql-graph-cli analyze --host localhost --port 3306 --username user --password pass --database mydb

Configuration Generation

sql-graph-cli config generate --output mydb-config.yml
sql-graph-cli config validate --config mydb-config.yml

Installation Options

From GitHub Releases

# Download binary for your platform
wget https://github.com/peter7775/sql-graph-visualizer/releases/download/v1.0.0/sql-graph-cli-linux-amd64
chmod +x sql-graph-cli-linux-amd64
sudo mv sql-graph-cli-linux-amd64 /usr/local/bin/sql-graph-cli

From Source

git clone https://github.com/peter7775/sql-graph-visualizer.git
cd sql-graph-visualizer
go build -o sql-graph-cli cmd/sql-graph-cli/main.go

Docker

docker-compose up -d

Key Benefits

For Database Administrators

Instant schema visualization and analysis
Security assessment of database connections
Performance insights and optimization recommendations
Non-intrusive read-only analysis

For Developers

Automatic rule generation for Neo4j transformation
Clean API for programmatic access
Flexible configuration with YAML
Comprehensive documentation and examples

For Data Scientists

Graph-based data analysis capabilities
Relationship discovery and pattern recognition
Interactive visualization with Neovis.js
Export capabilities for further analysis

Breaking Changes

This is the first release, so no breaking changes apply. However, note:

Project Rename

Project renamed from mysql-graph-visualizer to sql-graph-visualizer
CLI tool renamed from mysql-graph-cli to sql-graph-cli
This prepares for PostgreSQL support in upcoming releases

System Requirements

Minimum Requirements

Operating System: Linux, macOS, Windows
Go Version: 1.24+ (if building from source)
Source Database: MySQL 8.0+
Target Database: Neo4j 4.4+
Memory: 512MB RAM minimum
Disk Space: 100MB for installation

Recommended Requirements

Memory: 2GB RAM for optimal performance
CPU: Multi-core processor for parallel processing
Network: Stable connection for database access
Docker: For containerized deployment

Security

Connection Security

SSL/TLS validation and enforcement
Read-only access validation
Permission analysis and recommendations
Connection timeout and retry logic

Data Protection

No data modification - read-only operations only
Secure credential handling with environment variables
Audit logging of all database operations
Configurable access controls

Documentation

Available Documentation

README.md: Complete project overview and quick start
DIRECT_DATABASE_CONNECTION.md: Detailed technical documentation
Configuration examples: Multiple use case scenarios
CLI help: Built-in help system with --help flag

Getting Started

Download the appropriate binary for your platform
Test database connection: sql-graph-cli test --host ... --database ...
Analyze schema: sql-graph-cli analyze --host ... --database ...
Review generated transformation rules
Deploy to production with your Neo4j instance

Roadmap

Upcoming in v1.1.0 (PostgreSQL Support)

PostgreSQL database support (Issue #7)
Multi-database analysis capabilities
Enhanced CLI commands for PostgreSQL-specific features
Extended configuration options

Future Releases

v1.2.0: Advanced visualization features
v1.3.0: Real-time data synchronization
v1.4.0: Additional database engines (SQLite, Oracle)
v2.0.0: Reverse transformation (Neo4j → SQL)

Contributing

We welcome contributions! See our Contributing Guide for details.

How to Contribute

Fork the repository
Create feature branch: git checkout -b feature/amazing-feature
Add tests for new functionality
Ensure all tests pass: go test ./...
Submit pull request with detailed description

Areas for Contribution

PostgreSQL support implementation
Additional database drivers
Performance optimizations
Documentation improvements
Testing and quality assurance

Known Issues

Current Limitations

MySQL support only (PostgreSQL coming in v1.1.0)
Basic visualization (advanced features planned)
Single-database analysis (multi-database planned)

Workarounds

Use MySQL-compatible databases for now
Multiple CLI runs for multi-database analysis
External visualization tools for advanced features

Support

Community Support

GitHub Issues: Bug reports and feature requests
GitHub Discussions: Community questions and ideas
Documentation: Comprehensive guides and examples

Commercial Support

Enterprise licenses available for commercial use
Priority support and custom development
Training and consulting services

Contact: [email protected] for commercial licensing

Thank You!

Special thanks to:

Neo4j community for the excellent graph database
Go community for the robust development ecosystem
Early testers who provided valuable feedback
Contributors who helped shape this first release

Release Statistics

Development Time: 3 months
Code Lines: 15,000+ lines of Go code
Test Coverage: 85%+ with integration tests
Documentation: 50+ pages of comprehensive docs
Docker Images: Multi-platform support (linux/amd64, linux/arm64)

Download now and start transforming your SQL databases into powerful graph visualizations! 🚀

Made with ❤️ by the SQL Graph Visualizer Team

Uh oh!

Releases: peter7775/sql-graph-visualizer