Add Microsoft SQL Server Database Support

[peter7775]

Feature Request: Microsoft SQL Server Database Support

Summary

Add comprehensive Microsoft SQL Server support to the SQL Graph Visualizer, extending the existing multi-database architecture that currently supports MySQL and PostgreSQL.

Motivation

Microsoft SQL Server is one of the most widely used enterprise database systems. Adding SQL Server support would:

• Expand market reach to enterprise customers using SQL Server
• Enable legacy system modernization through graph visualization
• Complete the "Big 3" SQL database coverage (MySQL, PostgreSQL, SQL Server)
• Open opportunities in Microsoft-centric environments

Technical Requirements

Core Implementation

• SQL Server Driver Integration: Implement driver with connection pooling
• Repository Implementation: Create package
• Port Adaptation: Implement SQL Server-specific database port interface
• Factory Integration: Update database factory to support SQL Server selection
• Configuration Support: Add SQL Server configuration options with authentication methods

SQL Server Specific Features

• Authentication Methods: Windows Auth, SQL Server Auth, Azure AD
• Connection String Support: Handle complex SQL Server connection parameters
• Schema Discovery: SQL Server-specific metadata queries for tables/columns
• Data Type Mapping: Map SQL Server types to Neo4j properties appropriately
• Stored Procedure Support: Handle stored procedures in transformation rules

Configuration Example

Testing & Validation

• Unit Tests: SQL Server repository and connection tests
• Integration Tests: Full transformation pipeline with SQL Server
• Docker Environment: SQL Server container setup for development
• Sample Database: Northwind or similar sample database integration
• Validation Scripts: Automated testing with SQL Server sample data

Implementation Approach

Phase 1: Core Infrastructure

1. Add SQL Server driver dependency
2. Create basic repository structure
3. Implement connection management
4. Add configuration support

Phase 2: Query & Schema Support

1. Implement schema discovery
2. Add SQL Server-specific query execution
3. Handle data type conversions
4. Support for SQL Server metadata queries

Phase 3: Testing & Documentation

1. Comprehensive test suite
2. Docker development environment
3. Documentation and examples
4. Performance benchmarking

Success Criteria

• Can connect to SQL Server instances (local and remote)
• Successfully transforms SQL Server tables to Neo4j nodes
• Handles SQL Server-specific data types correctly
• Maintains performance comparable to MySQL/PostgreSQL implementations
• Comprehensive test coverage (>80%)
• Complete documentation with examples

Technical Considerations

Challenges

• Complex Authentication: SQL Server has multiple auth methods
• Connection Strings: More complex than MySQL/PostgreSQL
• Data Types: SQL Server has unique types (uniqueidentifier, hierarchyid, etc.)
• Enterprise Features: May need to handle advanced SQL Server features

Dependencies

• • Official Microsoft SQL Server driver
• Potential Azure-related packages for cloud authentication

Priority

High - SQL Server is a major enterprise database, this would significantly expand the project's reach.

Labels

, , , , ,

Related

• Follows the pattern established in Implement PostgreSQL Support #7 (PostgreSQL Support)
• Part of the multi-database architecture roadmap
• Could enable future Azure SQL Database support

---

Technical Complexity: High - requires understanding of SQL Server specifics and enterprise authentication
Expected Impact: High - opens up enterprise market segment
Community Benefit: High - many developers work with SQL Server in enterprise environments