---
name: database-fundamentals
description: Reviews schema design, SQL queries, ORM patterns. Use when junior creates schema, writes queries, adds migrations, works with Prisma/MongoDB/PostgreSQL, or asks "is this SQL safe", "N+1", "index".
---

# Database Fundamentals Review

> "Your database is the foundation. Build it wrong, and everything above it will crack."

## When to Apply

Activate this skill when reviewing:
- Schema design and migrations
- SQL/NoSQL queries
- ORM model definitions
- Data relationships
- Index creation
- Query performance

---

## Review Checklist

### Schema Design

- [ ] **Normalization**: Is data normalized appropriately (no excessive duplication)?
- [ ] **Denormalization justified**: If denormalized, is there a performance reason?
- [ ] **Primary keys**: Does every table have a clear primary key?
- [ ] **Foreign keys**: Are relationships enforced at the database level?
- [ ] **Data types**: Are appropriate types used (not everything TEXT)?

### Indexes

- [ ] **Query-based**: Are indexes created for frequently queried columns?
- [ ] **Composite indexes**: Are multi-column queries covered?
- [ ] **Not over-indexed**: Are there unnecessary indexes slowing writes?
- [ ] **Unique constraints**: Are unique fields enforced at DB level?

### Queries

- [ ] **No N+1**: Are related records fetched in bulk?
- [ ] **Select specific fields**: Are we avoiding `SELECT *`?
- [ ] **Pagination**: Do list queries limit results?
- [ ] **Parameterized**: Are all queries parameterized (no string concatenation)?

### Migrations

- [ ] **Reversible**: Can this migration be rolled back?
- [ ] **No data loss**: Will existing data survive the migration?
- [ ] **Tested**: Has this been tested against production-like data?
- [ ] **Incremental**: Are large changes broken into smaller migrations?

---

## Common Mistakes (Anti-Patterns)

### 1. The N+1 Query Problem
```
❌ // 1 query for users + N queries for posts
   const users = await User.findAll();
   for (const user of users) {
     user.posts = await Post.findAll({ where: { userId: user.id } });
   }

✅ // 1 query with JOIN
   const users = await User.findAll({
     include: [{ model: Post }]
   });

   // Or 2 queries with IN clause
   const users = await User.findAll();
   const userIds = users.map(u => u.id);
   const posts = await Post.findAll({ where: { userId: userIds } });
```

### 2. Missing Indexes
```
❌ // Queried frequently, but no index
   SELECT * FROM orders WHERE user_id = ?
   SELECT * FROM products WHERE category = ? AND status = 'active'

✅ CREATE INDEX idx_orders_user_id ON orders(user_id);
   CREATE INDEX idx_products_category_status ON products(category, status);
```

### 3. SELECT * Everywhere
```
❌ SELECT * FROM users; // Returns 50 columns

✅ SELECT id, name, email FROM users; // Only what's needed
```

### 4. String Concatenation (SQL Injection)
```
❌ db.query(`SELECT * FROM users WHERE email = '${email}'`);

✅ db.query('SELECT * FROM users WHERE email = ?', [email]);
```

### 5. Destructive Migrations
```
❌ -- Can't be rolled back
   DROP TABLE users;
   ALTER TABLE orders DROP COLUMN status;

✅ -- Add new, migrate data, then drop old (in separate migrations)
   -- Migration 1: Add new column
   ALTER TABLE orders ADD COLUMN status_new VARCHAR(20);
   -- Migration 2: Copy data
   UPDATE orders SET status_new = status;
   -- Migration 3: Drop old (after verification)
   ALTER TABLE orders DROP COLUMN status;
```

---

## Socratic Questions

Ask the junior these questions instead of giving answers:

1. **Schema**: "Why did you choose this data type?"
2. **Relationships**: "What happens if this related record is deleted?"
3. **Indexes**: "Which columns are queried together? Are they indexed?"
4. **N+1**: "How many queries does this operation execute?"
5. **Migration**: "What happens if we need to roll this back?"

---

## Normalization Quick Reference

| Form | Rule | Example Issue |
|------|------|---------------|
| 1NF | No repeating groups | `tags: "js,react,node"` should be separate table |
| 2NF | No partial dependencies | Order item price duplicated from products |
| 3NF | No transitive dependencies | Storing city AND zip code (zip determines city) |

### When to Denormalize

- Read-heavy workloads with rare writes
- Calculated aggregates (e.g., order totals)
- Caching frequently accessed derived data

---

## Index Strategy

```sql
-- Single column (most common)
CREATE INDEX idx_users_email ON users(email);

-- Composite (for multi-column queries)
-- Order matters! Most selective first
CREATE INDEX idx_orders_user_date ON orders(user_id, created_at);

-- Partial (for filtered queries)
CREATE INDEX idx_active_users ON users(email) WHERE active = true;

-- Unique (enforces constraint)
CREATE UNIQUE INDEX idx_users_email_unique ON users(email);
```

### Index Rules of Thumb

1. Index columns in WHERE clauses
2. Index columns in JOIN conditions
3. Index columns in ORDER BY (if used with WHERE)
4. Don't over-index write-heavy tables
5. Consider composite indexes for multi-column queries

---

## Query Optimization Checklist

1. [ ] Use EXPLAIN to analyze query plan
2. [ ] Avoid SELECT * - specify columns
3. [ ] Use LIMIT for pagination
4. [ ] Add indexes for WHERE/JOIN columns
5. [ ] Use WHERE instead of HAVING when possible
6. [ ] Avoid functions on indexed columns in WHERE
7. [ ] Use EXISTS instead of IN for large subqueries

---

## Red Flags to Call Out

| Flag | Question to Ask |
|------|-----------------|
| Query in a loop | "Can we fetch all this data in one query?" |
| No pagination | "What if there are 1 million records?" |
| SELECT * | "Do we need all 50 columns?" |
| String in query | "Is this protected against SQL injection?" |
| No indexes on foreign keys | "How fast are JOINs on this table?" |
| DROP TABLE in migration | "How do we roll this back?" |
| TEXT for everything | "Should this be an INT or DATE instead?" |
| No foreign key constraints | "What prevents orphaned records?" |

---

## ORM Best Practices

```typescript
// Eager loading (avoid N+1)
const users = await User.findAll({
  include: [{ model: Post, attributes: ['id', 'title'] }]
});

// Select specific fields
const users = await User.findAll({
  attributes: ['id', 'name', 'email']
});

// Pagination
const users = await User.findAll({
  limit: 20,
  offset: (page - 1) * 20
});

// Raw queries for complex operations
const results = await sequelize.query(
  'SELECT ... complex query ...',
  { type: QueryTypes.SELECT }
);
```


---
Source attribution: DanielPodolsky
Original project: https://github.com/DanielPodolsky/mentor-spec/blob/bd1f17c489aa3a2d7ef2b96889583e4f0a198e50/.claude/skills/fundamentals/database/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Daniel Podolsky

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: DanielPodolsky
Original project: https://github.com/DanielPodolsky/mentor-spec/blob/bd1f17c489aa3a2d7ef2b96889583e4f0a198e50/.claude/skills/fundamentals/database/SKILL.md
Attribution basis: Recovered original package and original project license at a pinned revision

Fields of work: Data & Analytics, Development & Engineering
Roles: Backend Developer, Data Analyst, Data Engineer, Database Administrator, ML / AI Engineer
Specialties: Database
Tools: MongoDB, MySQL, PostgreSQL, Redis, SQLite
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: fd81eeaed2d9a8174bc84f5d1db794de494c30253e1655ffa9958875945a9beb
Metadata reviewed: 2026-10-27
This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.