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If you’re seeking an ORM for NodeJS and MongoDB, look no further than Mongoose. This Node.js-based Object Data Modeling (ODM) library for MongoDB is akin to an Object Relational Mapper (ORM) such as SQLAlchemy. The problem that Mongoose aims to solve is allowing developers to enforce a specific schema at the application layer. In addition to enforcing a schema, Mongoose also offers a variety of hooks, model validation, and other features aimed at making it easier to work with MongoDB.
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spring-data-mongodb
Provide support to increase developer productivity in Java when using MongoDB. Uses familiar Spring concepts such as a template classes for core API usage and lightweight repository style data access.
See the Spring Data MongoDB documentation or the Spring Boot Integration with MongoDB Tutorial for more information.
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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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 a MongoDB ORM for Ruby, the Mongoid ODM provides API parity wherever possible to ensure developers working with a Rails application and using MongoDB can do so using methods and mechanics they’re already familiar with.
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Beanie is an Asynchronous Python object-document mapper (ODM) for MongoDB, based on Motor (an asynchronous MongoDB driver) and Pydantic.
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See the Mongoose documentation or MongoDB & Mongoose: Compatibility and Comparison for more information.
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
