Optimize Database Schema and Query Performance

[Drago-03]

Issue: Optimize Database Schema and Query Performance

Description

The current database schema has several inefficiencies that lead to performance issues, particularly as the dataset grows. There are missing indexes, suboptimal relationships between entities, and inefficient query patterns that cause slow responses under load.

Current Implementation Issues

• Missing indexes on frequently queried fields
• Inefficient schema design with redundant data
• No database-level constraints to ensure data integrity
• Lack of proper foreign key relationships
• Inefficient query patterns causing N+1 problems
• No database transaction handling for multi-step operations
• Poor handling of large result sets
• Inefficient text search implementation
• No database migrations strategy
• Inconsistent data access patterns across services

Proposed Solution

Implement a comprehensive database optimization that:

• Adds appropriate indexes for common query patterns
• Normalizes the schema to reduce redundancy
• Implements proper constraints and relationships
• Optimizes query patterns to prevent N+1 problems
• Adds transaction handling for data consistency
• Implements efficient pagination for large result sets
• Enhances text search capabilities
• Creates a formal migration strategy
• Standardizes data access patterns

Implementation Requirements

• Audit current database schema and identify optimization opportunities
• Create and apply missing indexes for common queries
• Refactor schema to normalize data where appropriate
• Implement proper foreign key constraints
• Optimize query patterns in data access layer
• Add transaction support for multi-step operations
• Implement cursor-based pagination for large collections
• Set up full-text search capabilities
• Create a migration framework for schema changes
• Develop standardized data access patterns

Acceptance Criteria

• Query performance improved by at least 50% for common operations
• All appropriate fields have indexes
• Data redundancy is minimized through proper normalization
• Referential integrity is enforced through constraints
• No N+1 query patterns in the codebase
• All multi-step operations use transactions
• Large result sets are efficiently paginated
• Text search is fast and relevant
• Schema changes can be applied through migrations
• Data access follows consistent patterns

Additional Notes

This optimization should be done carefully with thorough testing to ensure no regressions in functionality. Consider implementing changes incrementally, starting with the most impactful optimizations first.