Database Operations Manager

Usage Examples

Query Optimization

from scripts.query_builder import QueryBuilder

builder = QueryBuilder()
optimized = builder.optimize_query(
    "SELECT * FROM users WHERE age > 25",
    database_type="postgresql"
)
print(f"Original cost: {optimized['original_cost']}")
print(f"Optimized cost: {optimized['optimized_cost']}")

Schema Analysis

from scripts.schema_analyzer import SchemaAnalyzer

analyzer = SchemaAnalyzer()
schema_report = analyzer.analyze_schema({
    "tables": ["users", "orders", "products"],
    "database_type": "mysql"
})
print(f"Normalization: {schema_report['normalization_level']}")

Index Recommendations

from scripts.optimizer import Optimizer

optimizer = Optimizer()
recommendations = optimizer.recommend_indexes(
    "SELECT * FROM orders WHERE user_id = 123",
    database_type="postgresql"
)
print(f"Suggested indexes: {recommendations['indexes']}")

Connection Pool Management

from scripts.connection_manager import ConnectionManager

pool = ConnectionManager()
config = pool.optimize_pool_size(
    database_type="mysql",
    expected_connections=1000
)
print(f"Pool size: {config['pool_size']}")

Output Format

All modules return structured JSON:

{
  "analysis_type": "string",
  "original_query": "string",
  "optimized_query": "string",
  "performance_gain": "percentage",
  "index_recommendations": ["array"],
  "execution_plan": "string",
  "estimated_cost": number,
  "normalization_status": "1NF|2NF|3NF",
  "recommendations": ["array of actionable items"]
}

Severity Levels

Version & Support

• Version: 1.0.0
• Released: February 2026
• Status: Production Ready
• Confidence: 90%

Future Enhancements (v1.1.0)

• NoSQL optimization (MongoDB, DynamoDB)
• Sharding strategy recommendations
• Query caching suggestions
• Replication setup guidance
• Backup and recovery planning
• Multi-database migration tools
• Real-time performance monitoring integration
• Machine learning-based query prediction