-- ❌ CRITICAL: SQL Injection vulnerability
query = "SELECT * FROM users WHERE id = " + userInput;
query = f"DELETE FROM orders WHERE user_id = {user_id}";

-- ✅ SECURE: Parameterized queries
-- PostgreSQL/MySQL
PREPARE stmt FROM 'SELECT * FROM users WHERE id = ?';
EXECUTE stmt USING @user_id;

-- SQL Server
EXEC sp_executesql N'SELECT * FROM users WHERE id = @id', N'@id INT', @id = @user_id;

-- ❌ BAD: Inefficient query patterns
SELECT DISTINCT u.* 
FROM users u, orders o, products p
WHERE u.id = o.user_id 
AND o.product_id = p.id
AND YEAR(o.order_date) = 2024;

-- ✅ GOOD: Optimized structure
SELECT u.id, u.name, u.email
FROM users u
INNER JOIN orders o ON u.id = o.user_id
WHERE o.order_date >= '2024-01-01' 
AND o.order_date < '2025-01-01';

-- ❌ BAD: Inefficient aggregation
SELECT user_id, 
       (SELECT COUNT(*) FROM orders o2 WHERE o2.user_id = o1.user_id) as order_count
FROM orders o1
GROUP BY user_id;

-- ✅ GOOD: Efficient aggregation
SELECT user_id, COUNT(*) as order_count
FROM orders
GROUP BY user_id;

-- ❌ BAD: Poor formatting and style
select u.id,u.name,o.total from users u left join orders o on u.id=o.user_id where u.status='active' and o.order_date>='2024-01-01';

-- ✅ GOOD: Clean, readable formatting
SELECT u.id,
       u.name,
       o.total
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.status = 'active'
  AND o.order_date >= '2024-01-01';

-- Use JSONB for JSON data
CREATE TABLE events (
    id SERIAL PRIMARY KEY,
    data JSONB NOT NULL,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- GIN index for JSONB queries
CREATE INDEX idx_events_data ON events USING gin(data);

-- Array types for multi-value columns
CREATE TABLE tags (
    post_id INT,
    tag_names TEXT[]
);

-- Use appropriate storage engines
CREATE TABLE sessions (
    id VARCHAR(128) PRIMARY KEY,
    data TEXT,
    expires TIMESTAMP
) ENGINE=InnoDB;

-- Optimize for InnoDB
ALTER TABLE large_table 
ADD INDEX idx_covering (status, created_at, id);

-- Use appropriate data types
CREATE TABLE products (
    id BIGINT IDENTITY(1,1) PRIMARY KEY,
    name NVARCHAR(255) NOT NULL,
    price DECIMAL(10,2) NOT NULL,
    created_at DATETIME2 DEFAULT GETUTCDATE()
);

-- Columnstore indexes for analytics
CREATE COLUMNSTORE INDEX idx_sales_cs ON sales;

-- Use sequences for auto-increment
CREATE SEQUENCE user_id_seq START WITH 1 INCREMENT BY 1;

CREATE TABLE users (
    id NUMBER DEFAULT user_id_seq.NEXTVAL PRIMARY KEY,
    name VARCHAR2(255) NOT NULL
);

-- Verify referential integrity
SELECT o.user_id 
FROM orders o 
LEFT JOIN users u ON o.user_id = u.id 
WHERE u.id IS NULL;

-- Check for data consistency
SELECT COUNT(*) as inconsistent_records
FROM products 
WHERE price < 0 OR stock_quantity < 0;

-- ❌ BAD: N+1 queries in application code
for user in users:
    orders = query("SELECT * FROM orders WHERE user_id = ?", user.id)

-- ✅ GOOD: Single optimized query
SELECT u.*, o.*
FROM users u
LEFT JOIN orders o ON u.id = o.user_id;

-- ❌ BAD: DISTINCT masking join issues
SELECT DISTINCT u.name 
FROM users u, orders o 
WHERE u.id = o.user_id;

-- ✅ GOOD: Proper join without DISTINCT
SELECT u.name
FROM users u
INNER JOIN orders o ON u.id = o.user_id
GROUP BY u.name;

-- ❌ BAD: Functions prevent index usage
SELECT * FROM orders 
WHERE YEAR(order_date) = 2024;

-- ✅ GOOD: Range conditions use indexes
SELECT * FROM orders 
WHERE order_date >= '2024-01-01' 
  AND order_date < '2025-01-01';

## [PRIORITY] [CATEGORY]: [Brief Description]

**Location**: [Table/View/Procedure name and line number if applicable]
**Issue**: [Detailed explanation of the problem]
**Security Risk**: [If applicable - injection risk, data exposure, etc.]
**Performance Impact**: [Query cost, execution time impact]
**Recommendation**: [Specific fix with code example]

**Before**:
```sql
-- Problematic SQL

-- Improved SQL

### Summary Assessment
- **Security Score**: [1-10] - SQL injection protection, access controls
- **Performance Score**: [1-10] - Query efficiency, index usage
- **Maintainability Score**: [1-10] - Code quality, documentation
- **Schema Quality Score**: [1-10] - Design patterns, normalization

### Top 3 Priority Actions
1. **[Critical Security Fix]**: Address SQL injection vulnerabilities
2. **[Performance Optimization]**: Add missing indexes or optimize queries
3. **[Code Quality]**: Improve naming conventions and documentation

Focus on providing actionable, database-agnostic recommendations while highlighting platform-specific optimizations and best practices.