使用MongoDB搭配Django：选mongoengine.Document还是models.Model？

Hey there! Let's walk through the pros and cons of sticking with Django's models.Model versus switching to mongoengine.Document for your MongoDB integration, then wrap up with some practical advice to help you make the call.

First off, to use models.Model with MongoDB, you'll need a third-party adapter like django-mongodb-engine since Django's native ORM is built for relational databases. Here's how it stacks up:

Pros #

• Zero learning curve: You already know Django ORM's querysets, filters, annotations, and syntax—no need to pick up a new tool. If your team is all Django devs, this keeps everyone on the same page without extra training.
• Full Django ecosystem compatibility: You can plug your ViewerRequestLog directly into Django Admin, use Django forms, authentication, signals, and other built-in tools without modification. This is a huge win if your project is deeply tied to Django's ecosystem.
• Migration support: Even though MongoDB is schema-less, django-mongodb-engine works with Django's migrations system. This makes it easy to track field changes, collaborate with your team, and roll out updates consistently.

Cons #

• Limited MongoDB feature access: Django ORM is designed for tables and foreign keys, so MongoDB's strengths like nested documents, arrays, geospatial queries, and atomic updates are either clunky to implement or outright unavailable. For example, storing nested device info in ViewerRequestLog would force you to use a JSONField or split it into a separate model with a foreign key—wasting MongoDB's native document capabilities.
• Performance overhead: The translation layer between Django ORM and MongoDB adds extra latency, especially for complex queries. You'll miss out on the speed of MongoDB's native query language.
• Inflexible schema: Django ORM enforces a strict schema. If you need to add fields dynamically or adjust your data model on the fly, you'll have to run migrations every time—something MongoDB is built to avoid.

Mongoengine is an ORM built specifically for MongoDB, so it's tailored to document-based data models. Here's what you get:

Pros #

• Native MongoDB feature support: You can directly use nested documents (EmbeddedDocumentField), arrays, geospatial indexes, aggregation pipelines, and atomic operations. For your ViewerRequestLog, this means you can store user agent, device info, and request metadata all in a single document without workarounds.
• Clean, MongoDB-aligned syntax: The API is designed to mirror MongoDB's native query language, so complex operations feel intuitive. Writing aggregations or filtering nested fields is straightforward, no need to translate Django ORM logic to MongoDB.
• Dynamic schema flexibility: Mongoengine supports DynamicDocument, which lets you add fields to documents at runtime without schema migrations. This is perfect for projects where requirements change frequently.

Cons #

• Learning curve: You'll need to learn Mongoengine's syntax and patterns, even if you know Django ORM. While there are similarities (like querysets), there are key differences in field types, query methods, and schema management.
• Django ecosystem friction: Mongoengine doesn't play nicely with Django's built-in tools out of the box. You'll need third-party extensions (like mongoengine-django-admin) to use Django Admin, and forms/authentication will require custom setup. This can introduce bugs and extra maintenance work.
• No built-in migrations: Unlike Django ORM, Mongoengine doesn't have a native migration system. You'll have to manually handle field updates and schema changes across your database, which can lead to inconsistencies in team environments.

Here's how to decide based on your project's needs:

• Stick with models.Model if: Your project is heavily dependent on Django's ecosystem (Admin, forms, auth), you only need basic MongoDB functionality, and you want to keep your codebase consistent with existing Django practices.
• Switch to mongoengine.Document if: Your core business logic relies on MongoDB's document-specific features (nested data, complex aggregations), you're building a new project centered around MongoDB, or you need the flexibility of dynamic schemas.
• Hybrid approach: If you have a mix of relational and document data, you can use both ORMs. Just be careful to isolate their contexts (e.g., separate database connections) to avoid conflicts with transactions or connection pools.

To make the difference concrete, here's how your ViewerRequestLog might look in both:

# mongoengine.Document
from mongoengine import Document, StringField, EmbeddedDocumentField, DateTimeField
import datetime

class DeviceInfo(EmbeddedDocument):
    os = StringField()
    browser = StringField()

class ViewerRequestLog(Document):
    request_id = StringField(required=True, unique=True)
    user_agent = StringField()
    device_info = EmbeddedDocumentField(DeviceInfo)  # Native nested document
    created_at = DateTimeField(default=datetime.datetime.now)

# models.Model (with django-mongodb-engine)
from django.db import models

class ViewerRequestLog(models.Model):
    request_id = models.CharField(max_length=255, unique=True)
    user_agent = models.CharField(max_length=255, blank=True)
    device_info = models.JSONField()  # Workaround for nested data
    created_at = models.DateTimeField(auto_now_add=True)

内容的提问来源于stack exchange，提问作者NeedAnAnswere