Amazon DocumentDB vs. Azure SQL Database vs. Mongoose vs. NoSQL Manager Comparison Chart

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs).

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.