I have seen this and other similar titled questions, none answer my question.
I was going through the mongoose documentation where I read
MongoDB has the join-like $lookup aggregation operator in versions >=
3.2. Mongoose has a more powerful alternative called populate(), which lets you reference documents in other collections.
How does populate() in mongoose work that makes it more powerful than MongoDB's $lookup?
Isn't mongoose a tool that helps nodejs users work with mongodb. If so how can mongoose have functionalities that MongoDB does not? Like populate()?
Does mongoose's populate() method use MongoDB's $lookup behind the scenes?
Thanks to a github thread shared by Grégory NEUT in the question's comments I have been able to establish certain facts:
Mongoose's populate() method does not use MongoDB's $lookup behind the scenes. It simply makes another query to the database.
Mongoose does not have functionalities that MongoDB does not have. populate() just makes two or more queries.
How does populate() in mongoose work that makes it more powerful than
MongoDB's $lookup?
In my opinion, there are places to use populate() and others to use $lookup. For more complex queries $lookup in an aggregation pipeline would work best.
I have a server which stores records representing Objects, and which uses Mongoose to manage these records. I want to be able to query/update/etc. all objects with a simple API (i.e. a single endpoint). Different types of Objects have some identical attributes, and some different attributes, so a single, static Object schema won't do. Instead, I still want to have a single schema, but I want to be able to change it slightly by adding/deleting fields when I create each new Object, with the fields which are/aren't present depending on the type of the Object. I don't want a mixed schema, because I want error validation for each type of Object. I want a single schema (as opposed to a different schema for each type of Object) so that I can just do
Object = mongoose.model('Object', ObjectSchema);
Object.findOne({objectType: "type1"}, function(err, model) {
...
});
So basically, I want field validation, while still maintaining some flexibility for attributes, and a single point to query/update/etc. my Object records. If I change the schema with each new Object, recompile it into a model, and create a new instance of that model, will all the instances of the different models (compiled from different modified versions of the same schema) still be queryable as above?
Obviously, I'm new to Mongoose. I just talked a lot about the schema here, and I honestly don't know whether I should have used the word "model" in place of "schema" in some places. I just don't know how I can accomplish all of this. Let me know if I make no sense.
We are successfully using the mongoose model inheritance and discriminator functionality for a very similar scenario. See here for an example:
http://www.laplacesdemon.com/2014/02/19/model-inheritance-node-js-mongoose/
You might also be able to use this plugin:
https://www.npmjs.com/package/mongoose-schema-extend
When looking at tutorials there is often a delineation between a schema and a model, particularly when dealing with mongoose/mongodb.
This makes porting over to postgresql somewhat confusing, as 'models' don't seem to exist under that system. What is the difference the two approaches?
For example, what would be a postgres/sql ORM equivalent of this line?
(mongoose and express.js):
var userSchema = schema.define('local', {
username: String,
password: String,
});
module.exports = mongoose.model('User', userSchema);
In mongoose, a schema represents the structure of a particular document, either completely or just a portion of the document. It's a way to express expected properties and values as well as constraints and indexes. A model defines a programming interface for interacting with the database (read, insert, update, etc). So a schema answers "what will the data in this collection look like?" and a model provides functionality like "Are there any records matching this query?" or "Add a new document to the collection".
In straight RDBMS, the schema is implemented by DDL statements (create table, alter table, etc), whereas there's no direct concept of a model, just SQL statements that can do highly flexible queries (select statements) as well as basic insert, update, delete operations.
Another way to think of it is the nature of SQL allows you to define a "model" for each query by selecting only particular fields as well as joining records from related tables together.
In other ORM systems like Ruby on Rails, the schema is defined via ActiveRecord mechanisms and the model is the extra methods your Model subclass adds that define additional business logic.
A schema is fundamentally describing the data construct of a
document (in MongoDB collection). This schema defines the name of each item of data, and the type of data, whether it is a string, number, date, Boolean, and so on.
A model is a compiled version of the schema. One instance of the model will map to one document in the database.
It is the model that handles the reading, creating, updating, and deleting of documents.
A document in a Mongoose collection is a single instance of a model. So it makes sense that if we're going to work with our data then it will be through the model.
A single instance of a model (like a User instance in var User = mongoose.model('User', userSchema);) maps directly to a single document in the database.
With this 1:1 relationship, it is the model that handles all document interaction - creating, reading, saving, and deleting. This makes the model a very powerful tool.
Taken from "Mongoose for Application Development", by Simon Holmes, 2013
I imagine models as classes created from a schema (maybe I am mistaken).
MongoDB stores everything in BSON , which is a binary format. A simple Hello World BSON document might look like this internally:
\x16\x00\x00\x00\x02hello\x00\x06\x00\x00\x00world\x00\x00. A computer can deal with all that mumbo-jumbo, but that's hard to read for humans. We want something we can easily understand, which is why developers have created the concept of a database model. A model is a representation of a database record as a nice object in your programming language of choice. In this case, our models will be JavaScript objects. Models can serve as simple objects that store database values, but they often have things like data validation, extra methods, and more. As you’ll see, Mongoose has a lot
of those features.
Taken from "Express in Action", by Evan Hahn, 2016
In Short:
A Mongoose model is a wrapper on the Mongoose schema. A Mongoose schema defines the structure of the document, default values, validators, etc., whereas a Mongoose model provides an interface to the database for creating, querying, updating, deleting records, etc.
Reference: Introduction to Mongoose for MongoDB - FCC
If I define a nested model or a relation in a mongoose schema, does it have a mechanism to autoload everything when re-hydrating instances, or do I simply have to ensure I've always loaded the appropriate models?
Nested, embedded model docs are auto-loaded, but if it's an ObjectId based relation, then you need to use Mongoose's populate support to explicitly load the related docs.
Mongoose performs all these actions based on the schemas and models that your code defines, typically during your app's startup.
Looking at the Mongoose ODM docs, it doesn't really say much about what are ObjectId's and how they can be used. I think its something like foreign keys in MongoDB?
If so, Embedded Documents seem to achieve the same purpose, when do I use which?
It would be very worthwhile to read the MongoDB documentation or a quick MongoDB intro such as The Little MongoDB Book (it's free) for some background on MongoDB concepts.
To answer your question:
An ObjectID is a unique 12-byte identifier which can be generated by MongoDB as the primary key (_id) for a collection. There is a specification for the ObjectID.
A DBRef (database reference) is an ObjectID referencing an object in another collection. A DBRef does require require another query to fetch the related object, and is a convention supported by the client drivers rather than MongoDB server. The Mongoid equivalent is called referenced relations.
Embedded documents are nested arrays or subdocuments within a document. In Mongoid these are embedded relations.
The approach to data modelling and schema design in MongoDB is very different from relational databases. There are (intentionally) no joins or foreign keys, but the document-oriented approach allows large amounts of related data to be stored and fetched in a single document. Depending on how you plan to query and update your data, embedding or linking may be a more suitable choice. The schema design page on the MongoDB wiki has some helpful tips to get you started.