Amazon DocumentDB vs. Mongoose vs. NoSQL Manager vs. Oracle SQL Developer Data Modeler Comparison Chart

Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Now say we like fuzzy kittens and want to record every kitten we ever meet in MongoDB. The first thing we need to do is include mongoose in our project and open a connection to the test database on our locally running instance of MongoDB. We have a pending connection to the test database running on localhost. We now need to get notified if we connect successfully or if a connection error occurs. Mongoose documents represent a one-to-one mapping to documents as stored in MongoDB. Each document is an instance of its Model. Subdocuments are documents embedded in other documents. In Mongoose, this means you can nest schemas in other schemas. Mongoose has two distinct notions of subdocuments: arrays of subdocuments and single nested subdocuments.

Oracle SQL Developer Data Modeler is a free graphical tool that enhances productivity and simplifies data modeling tasks. Using Oracle SQL Developer Data Modeler users can create, browse and edit, logical, relational, physical, multi-dimensional, and data type models. The Data Modeler provides forward and reverse engineering capabilities and supports collaborative development through integrated source code control. The Data Modeler can be used in both traditional and in Cloud environments. Oracle SQL Developer Data Modeler is one of the database tools in the Oracle Database Tools group. It is an independent, standalone product with a full spectrum of data and database modeling tools and utilities. There is a general FAQ and other supporting collateral on the Data Modeler home page. This document is to provide some guidance to the pricing-related questions arising in the community.