databases

Files (19)

• SKILL.md
• mongodb-aggregation.md · references/
• mongodb-atlas.md · references/
• mongodb-crud.md · references/
• mongodb-indexing.md · references/
• postgresql-administration.md · references/
• postgresql-performance.md · references/
• postgresql-psql-cli.md · references/
• postgresql-queries.md · references/
• .coverage · scripts/
• db_backup.py · scripts/
• db_migrate.py · scripts/
• db_performance_check.py · scripts/
• requirements.txt · scripts/
• coverage-db.json · scripts/tests/
• requirements.txt · scripts/tests/
• test_db_backup.py · scripts/tests/
• test_db_migrate.py · scripts/tests/
• test_db_performance_check.py · scripts/tests/

SKILL.md (first lines)

# Databases Skill

Unified guide for working with MongoDB (document-oriented) and PostgreSQL (relational) databases. Choose the right database for your use case and master both systems.

## When to Use This Skill

Use when:

- Designing database schemas and data models
- Writing queries (SQL or MongoDB query language)
- Building aggregation pipelines or complex joins
- Optimizing indexes and query performance
- Implementing database migrations
- Setting up replication, sharding, or clustering
- Configuring backups and disaster recovery
- Managing database users and permissions
- Analyzing slow queries and performance issues
- Administering production database deployments

## Database Selection Guide

### Choose MongoDB When:

- Schema flexibility: frequent structure changes, heterogeneous data
- Document-centric: natural JSON/BSON data model
- Horizontal scaling: need to shard across multiple servers
- High write throughput: IoT, logging, real-time analytics
- Nested/hierarchical data: embedded documents preferred
- Rapid prototyping: schema evolution without migrations

**Best for:** Content management, catalogs, IoT time series, real-time analytics, mobile apps, user profiles

### Choose PostgreSQL When:

- Strong consistency: ACID transactions critical
- Complex relationships: many-to-many joins, referential integrity
- SQL requirement: team expertise, reporting tools, BI systems
- Data integrity: strict schema validation, constraints
- Mature ecosystem: extensive tooling, extensions
- Complex queries: window functions, CTEs, analytical workloads

**Best for:** Financial systems, e-commerce transactions, ERP, CRM, data warehousing, analytics

### Both Support:

- JSON/JSONB storage and querying
- Full-text search capabilities
- Geospatial queries and indexing
- Replication and high availability
- ACID transactions (MongoDB 4.0+)
- Strong security features

## Quick Start

### MongoDB Setup

```bash
# Atlas (Cloud) - Recommended
# 1. Sign up at mongodb.com/atlas
# 2. Create M0 free cluster
# 3. Get connection string

# Connection
mongodb+srv://user:pass@cluster.mongodb.net/db

# Shell
mongosh "mongodb+srv://cluster.mongodb.net/mydb"

# Basic operations
db.users.insertOne({ name: "Alice", age: 30 })
db.users.find({ age: { $gte: 18 } })
db.users.updateOne({ name: "Alice" }, { $set: { age: 31 } })
db.users.deleteOne({ name: "Alice" })
```

### PostgreSQL Setup

```bash
# Ubuntu/Debian
sudo apt-get install postgresql postgresql-contrib

# Start service
sudo systemctl start postgresql

# Connect
psql -U postgres -d mydb

# Basic operations
CREATE TABLE users (id SERIAL PRIMARY KEY, name TEXT, age INT);
INSERT INTO users (name, age) VALUES ('Alice', 30);
SELECT * FROM users WHERE age >= 18;
UPDATE users SET age = 31 WHERE name = 'Alice';
DELETE FROM users WHERE name = 'Alice';
```

## Common Operations

### Create/Insert

```javascript
// MongoDB
db.users.insertOne({ name: "Bob", email: "bob@example.com" });
db.users.insertMany([{ name: "Alice" }, { name: "Charlie" }]);
```

```sql
-- PostgreSQL
INSERT INTO users (name, email) VALUES ('Bob', 'bob@example.com');
INSERT INTO users (name, email) VALUES ('Alice', NULL), ('Charlie', NULL);
```

### Read/Query

```javascript
// MongoDB
db.users.find({ age: { $gte: 18 } });
db.users.findOne({ email: "bob@example.com" });
```

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