MongoDB Features

MongoDB is a document-oriented database that makes the scaling very easier. It replaces the concept of "row" with more flexible "document".
Relational databases are very difficult to scale, the MongoDB scales easily and capable of storing rich data structures.
In a relational database, first we need to create the structure before capturing data. But using mongodb, we can easily insert data whose structure can't be known in advance.
MongoDB uses the BSON binary format.
The key-value structure offers a flexible data model, dynamic modification of schema and allows to store and combine data of any structure.
It is well suited as a primary data storage for modern web applications.
It supports secondary indexes, allowing a variety of fast queries and full text indexing as well.
We can run complex aggregations from a simple code.
It is schema-less, no need to configure the database column with types.
It provides native drivers for all popular programming languages and frameworks.
It offers a range of tools for interacting with the database, independent of the drivers.
Mongodb is not only limited to simple key-value operations. The developers can build advanced applications using aggregations, complex queries and secondary indexes.
Most of the applications are working on object-oriented languages, and so developers want a database that maps to objects better. MongoDB fulfills this requirement.
To handle the failure of server outages, it provides Replica-set, which distribute data across machines for redundancy and handle server failure. It consists of one primary node and one or more secondary nodes.
MongoDB provides horizontal scale out for databases using a technique called Auto-Sharding. It distributes data across multiple partitions called shards.

MongoDB Terms

Let's know the terms used in a document-oriented database with an example -

db.book.insert({ _id: ObjectID('8sf332f3dcefd644108961bb'),
title: 'MongoDb Features',
url: 'https://www.etutorialspoint.com',
author: 'etutorialspoit',
views: 2000,
tags: ['mongodb', 'nosql', 'document-based']
});

Collection: Collection in MongoDB is an analog of a table in a relational database. It is a group of documents. Each document in a collection can have different structures. A collection can contain up to 64 indexes.

> db.employee.insert({name:"Priska",dept:"IT",role:"developer"});

In the above example, 'employee' is a collection.

Document: A document is equivalent to a row in a relational database and it is essentially a set of property names and their values. MongoDB stores data as documents in BSON.

{name:"Priska",dept:"IT",role:"developer"}

The above document contains three key-value pairs.

ObjectId: Every document in MongoDB must have a unique id (_id key). ObjectId is a default type that automatically generates a unique id if not specified for _id.

{
"_id" : ObjectId(),
"key" : "value"
}

Key: The keys in a document are strings. It does not contain null character.

Value: The value can be simple or complex data types, such as strings, numbers, dates, array. It can also be other documents.

Indexing: MongoDB provides secondary indexes, which are implemented as B-trees and also provides unique, compound, full-text indexing capabilities as well.