diegosouzapw NoSQL Patterns
Expert patterns for working with NoSQL databases (MongoDB, Redis, DynamoDB, etc.)
When to Use This Skill
- MongoDB document database design
- Redis caching and data structures
- DynamoDB single-table design
- NoSQL performance optimization
- Choosing SQL vs NoSQL
Content Map
MongoDB
- mongodb-patterns.md - Document modeling
- Schema design patterns
- Indexing strategies
- Aggregation pipelines
- Transactions
Redis
- redis-patterns.md - Caching strategies
- Data structures (String, Hash, List, Set, Sorted Set)
- Pub/Sub patterns
- Session storage
- Rate limiting
DynamoDB
- dynamodb-patterns.md - Single-table design
- Partition & sort keys
- GSI/LSI strategies
- Query optimization
Performance
- performance.md - Indexing best practices
- Query optimization
- Sharding strategies
- Connection pooling
Quick Reference
MongoDB Document Design
// ✅ Good - Embedded for 1-to-few
{
_id: ObjectId("..."),
name: "John Doe",
email: "john@example.com",
addresses: [
{ street: "123 Main", city: "NYC", zip: "10001" },
{ street: "456 Oak", city: "LA", zip: "90001" }
]
}
// ✅ Good - Referenced for 1-to-many
{
_id: ObjectId("..."),
title: "Post Title",
authorId: ObjectId("..."), // Reference to User
comments: [ObjectId("..."), ObjectId("...")] // References
}
MongoDB Aggregation
db.orders.aggregate([
{ $match: { status: "completed" } },
{ $group: {
_id: "$userId",
totalSpent: { $sum: "$amount" },
orderCount: { $sum: 1 }
}},
{ $sort: { totalSpent: -1 } },
{ $limit: 10 }
]);
Redis Caching Pattern
async function getUser(userId) {
// Try cache first
const cached = await redis.get(`user:${userId}`);
if (cached) return JSON.parse(cached);
// Cache miss - fetch from DB
const user = await db.users.findById(userId);
// Store in cache (TTL: 1 hour)
await redis.setex(`user:${userId}`, 3600, JSON.stringify(user));
return user;
}
Redis Data Structures
// Counter
await redis.incr('page:views');
// Set (unique items)
await redis.sadd('users:online', userId);
await redis.sismember('users:online', userId);
// Sorted Set (leaderboard)
await redis.zadd('leaderboard', score, userId);
await redis.zrevrange('leaderboard', 0, 9); // Top 10
Anti-Patterns
❌ Treating NoSQL like SQL → Embrace denormalization
❌ No indexing → Critical for performance
❌ Deep nesting → Limit to 2-3 levels
❌ Large arrays → Use references for > 100 items
❌ No TTL on cache → Memory leaks
Best Practices
✅ Embed for 1-to-few, reference for 1-to-many
✅ Index frequently queried fields
✅ Use aggregation pipelines for complex queries
✅ Implement caching layer (Redis)
✅ Set TTL on cached data
✅ Monitor query performance
When to Use
Use NoSQL when:
- Flexible/evolving schema
- Horizontal scaling needed
- High write throughput
- Document/graph data model fits
Use SQL when:
- Complex joins required
- ACID transactions critical
- Structured, relational data
- Strong consistency needed