Although developers have always been able to manually write complex queries to interact with a database, this approach can be tedious and error-prone. Object-relational mappers (or ORMs) improve the developer experience, as they accomplish a number of meaningful tasks:
- Facilitating interaction between the database and the application by removing the need to write raw SQL or a database query language.
- Manage serialization/deserialization of data for objects.
- Implementation of schema.
So, while it is true that MongoDB provides idiomatic APIs and helpers to drivers for most programming languages, sometimes a higher level abstraction is desirable. Developers are used to interacting with data in a more declarative fashion (LINQ for C#, ActiveRecord for Ruby, etc.) and an ORM facilitates code maintenance and allows developers to access data as objects. allows you to interact with.
MongoDB offers several ORM-like libraries, and so do our community and partners! These are sometimes referred to as ODM (Object Document Mapper), as MongoDB is not a relational database management system. However, they exist to solve the same problem as ORMs do and the terminology can be used interchangeably.
The following are some examples of the best MongoDB ORM or ODM libraries for multiple programming languages, including Ruby, Python, Java, Node.js and PHP.
Beanie is an asynchronous Python object-document mapper (ODM) for MongoDB, based on Motor (an asynchronous MongoDB driver) and Pydentic.
When using Pigtail, each database collection has an associated document that is used to interact with that collection. In addition to retrieving data, Plat allows you to add, update and delete documents from the archive. Beanie saves you time by removing boilerplate code, and it helps you focus on the parts of your app that really matter.
See beanie documentation for more details.
Doctrine is a PHP MongoDB ORM, even though it is referred to as an ODM. This library provides PHP object mapping functionality and transparent persistence to PHP objects to MongoDB, as well as a mechanism for mapping embedded or referenced documents. It can also create references between PHP documents in different databases and work with GridFS buckets.
See Doctrine MongoDB ODM documentation for more details.
Most Ruby-based applications are built using the Ruby on Rails framework. As a result, Rails’ Active Record implementation, conventions, CRUD API, and callback mechanisms are second nature to Ruby developers. So, as far as there is a MongoDB ORM for Ruby, Mongoid ODM provides API parallelism to ensure that developers working with Rails applications and using MongoDB can use the methods and methods they are already familiar with. You can do this using mechanics.
See Mongoid docs for more details.
If you are looking for ORM for NodeJS and MongoDB, look no further than Mongoose. This Node.js-based Object Data Modeling (ODM) library for MongoDB is similar to an object relational mapper (ORM) such as SQLAlchemy. The problem Mongoose aims to solve is by allowing developers to enforce a specific schema at the application layer. In addition to implementing a schema, Mongoose also provides a variety of hooks, model validation, and other features that aim to make working with MongoDB easier.
For more information see the Mongoose documentation or MongoDB and Mongoose: Compatibility and Comparison.
MongoEngine is a Python ORM for MongoDB. Branded as Document-Object Mapper, it uses a simple declarative API, similar to the Django ORM.
It was first released as an open-source project in 2015, and the current version is built by MongoDB on top of the official Python driver, pymongo.
See MongoEngine documentation for more details.
Support for MongoDB was one of the most requested features since the initial release of Prisma ORM, and was added in version 3.12.
See Prisma and MongoDB for more details.
Spring Data MongoDB
If you are looking for Java ORM for MongoDB, Spring Data for MongoDB is the most popular choice for Java developers. The Spring Data Project provides a familiar and consistent Spring-based programming model for new datastores while maintaining store-specific features and capabilities.
The key functional areas of Spring Data MongoDB that Java developers will benefit from are the POJO centric model for interacting with a MongoDB DBCollection and easily writing a repository-style data access layer.
For more information see the Spring Data MongoDB documentation or the Spring Boot Integration with MongoDB tutorial.
Go make something great!
While there is not an exhaustive list of MongoDB ORM and ODM libraries available right now, the entries above will allow you to start using MongoDB in your language of choice more naturally and efficiently.
If you’re looking for help or have any feedback don’t hesitate to join our community forums.