NoSQL Concepts: Document Databases

Document Databases

Schemaless
Store data in documents and these documents are grouped into collection
If you are familiar with relational databases we can say documents are analogous to rows and collections are analogous to table

Documents

Set of key-value pairs
Key: string
Value: number, string, booleans, arrays, objects
Polymorphic model it's means that documents within the same collection don't needt to have the same structure
Formats: JSON, BSON, YAML, XML

JSON document format

{  
  "user_id": 512,
  "name": "Carol", 
  "last_name": "Harper",
  "email": "carolharper@datazy.com",
  "address": { 
  "street": "123 Sesame Street",
  "city": "New York City", 
  "state": "New York",  
  "country": "USA"  },
  "hobbies": [   
  "hiking", "painting"
  ]
}

The value of "address" key is another document, notice that is related information is embedded in the main document, so don't need for searching about address in another document

Collections

Set of documents
Store the same type of entities

Advantages of document databases

Flexibility
- Don't need to predefine the schema
- Documents can vary over time => avoid schema migrations
- Embedded documents => avoid joins
Intuitive for developers
- Natural way to work
- JSON is human-readable
- Documents map objects in code
Horizontal scalability

Limitations of document databases

More responsibility
- Care about data in the application code
- Care about redundant data

The most popular document databases is "Mongo DB"

Ahmed Atya