When I learned SQL, the way to address was to create a series of tables (neighborhoods, cities, states, countries). Then he related the tables. So just add the id of the neighborhood to the record in question (client, supplier, collaborator ...) and the rest was the basis of the "inner join". Now, I started using mongodb. It is possible to obtain similar result with several collections, analogously to the SQL in the mongo, executing a series of callbacks in the find. Is this a best practice, or should I add all fields directly in the registry, or is there some other better procedure?
What is the correct way to structure addresses in mongodb?
3
asked by anonymous 27.02.2016 / 03:05
1 answer
1
I believe there is no correct answer in either RDBMS (SQL) or NoSQL. The design of the data will always depend on the purpose of your system.
If you are developing something that catalogs geographical entities (cities, streets, neighborhoods) type Google Maps or some delivery service, then it may make ultra-normalize sense to the street level and block.On the other hand, if you are only collecting customer addresses, and only need a single address, type Charges Address , it would be much simpler to put the address , , city , parent in the client table itself.
Likewise it is in the mongo. You can store collections of cities, neighborhoods, etc. (eg a {_id:1, nome: 'Centro', cep: '12345-123', id_cidade: 123} neighborhood) and refer to another collection (ex: {_id: 456, nome: 'Restaurante da Praça', endereco: {rua: 'Av Tancredo Neves, 333, sala 14', id_bairro: 1} } client). Or you can just nest everything (ex, client {_id: 456, nome: 'Restaurante da Praça', endereco: {rua: 'Av Tancredo Neves, 333, sala 14', bairro: 'Centro', cidade: 'Patópolis', uf: 'XY', pais: 'Disney World', cep: '12345-123'} } ).
In both cases (relational x nosql) there are advantages and disadvantages. It is up to you to analyze factors such as how and how often this data will be accessed and modified, impact on application performance, data maintenance difficulty, disk data size, etc.
My advice goes to start simple, revisit and improve if you need .
19.10.2016 / 17:26