A collection of practical SQL Server scripts covering real-world database operations, troubleshooting, and schema management patterns.
This repository is structured as a reference toolkit for database engineers, data scientists, or backend developers working with relational systems.
It focuses on applied SQL patterns rather than isolated examples.
- Safely dropping a column without breaking dependencies
- Diagnosing slow queries via active session inspection
- Bulk importing Excel data into staging tables
- Temporarily disabling constraints during data migrations
Scripts are grouped by operational domain:
System-level configuration and advanced SQL Server features.
- Enable ad-hoc distributed queries
- Enable
xp_cmdshell
Reusable utility patterns for data manipulation.
- Bulk insert patterns (Excel import scenarios)
- Duplicate detection and cleanup
Schema introspection and relational analysis.
- Foreign key relationship discovery
- Constraint mapping and dependency analysis
- Column reference tracing
Error handling and auditing patterns for production systems.
- Error logging table design
- Stored procedure logging patterns
- Transaction tracking examples
Database introspection utilities.
- Schema metadata extraction
- Object size and structure analysis
Core SQL execution patterns and maintenance scripts.
- Cursor-based processing examples
- Dynamic SQL execution patterns
- Merge operations
- Schema/table manipulation utilities
Production debugging and operational diagnostics.
- Active session monitoring
- Connection counting
- Constraint enable/disable workflows
- Statistics cleanup
- Login troubleshooting utilities
This repository is intended to demonstrate:
- practical SQL Server operational knowledge
- debugging and triage techniques used in production environments
- schema analysis and dependency tracing
- real-world database maintenance patterns
It is a working reference of SQL patterns used in backend and data engineering contexts.
Each script can be executed independently in a SQL Server environment such as:
- SQL Server Management Studio (SSMS)
- Azure Data Studio
Scripts are self-contained and designed to be copy/paste executable with minimal modification.
Contributions are welcome. Please ensure scripts:
- are production-relevant or educationally meaningful
- include clear naming and intent
- follow SQL Server best practices where applicable
MIT