Apache CouchDB

// CouchDB bruger HTTP API og MapReduce views

// 1. Opret database (HTTP PUT)
PUT http://localhost:5984/products

// 2. Indsæt document (HTTP POST)
POST http://localhost:5984/products
Content-Type: application/json

{
  "_id": "laptop-001",
  "type": "product",
  "name": "Lenovo ThinkPad",
  "price": 8999,
  "category": "laptops",
  "stock": 25,
  "tags": ["electronics", "computers"]
}

// 3. Hent document (HTTP GET)
GET http://localhost:5984/products/laptop-001

// 4. Definer view med MapReduce (design document)
PUT http://localhost:5984/products/_design/products
{
  "_id": "_design/products",
  "views": {
    "by_category": {
      "map": "function(doc) { if (doc.category) { emit(doc.category, doc.price); } }",
      "reduce": "_sum"
    },
    "by_price": {
      "map": "function(doc) { if (doc.price) { emit(doc.price, doc); } }"
    },
    "expensive_products": {
      "map": "function(doc) { if (doc.price > 5000) { emit(doc.name, doc.price); } }"
    }
  }
}

// 5. Query view
GET http://localhost:5984/products/_design/products/_view/by_category

// 6. Query med parameters
GET http://localhost:5984/products/_design/products/_view/by_category?key="laptops"

// 7. Range query
GET http://localhost:5984/products/_design/products/_view/by_price?startkey=5000&endkey=10000

// 8. Update document
PUT http://localhost:5984/products/laptop-001
{
  "_id": "laptop-001",
  "_rev": "1-967a00dff5e02add41819138abb3284d",
  "type": "product",
  "name": "Lenovo ThinkPad",
  "price": 7999,
  "category": "laptops",
  "stock": 20
}

// 9. Delete document
DELETE http://localhost:5984/products/laptop-001?rev=2-abc123...

// 10. Continuous changes feed
GET http://localhost:5984/products/_changes?feed=continuous

// JavaScript (Node.js) example med nano library
const nano = require('nano')('http://localhost:5984');
const db = nano.db.use('products');

// Insert
await db.insert({
  name: 'MacBook Pro',
  price: 15999,
  category: 'laptops'
});

// Query view
const result = await db.view('products', 'by_category', {
  key: 'laptops'
});

console.log(result.rows);