A NoSQL Database: MongoDB

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With the rise in data all around the world, there has been an observable and increasing interest surrounding the wave of the non-relational database, also known as ‘NoSQL. ‘ Businesses and organizations are seeking new methods to manage the flood of data and are drawn toward the alternate database management tools and systems that are different from the traditional relational database systems. Here comes MongoDB into the picture. 

What Is MongoDB? 

As a definition, MongoDB is an open-source database that uses a document-oriented data model and a non-structured query language. It is one of the most powerful NoSQL systems and databases around today. 

MongoDB Atlas is a cloud database solution for contemporary applications that is available globally. This best-in-class automation and established practices offer to deploy fully managed MongoDB across AWS, Google Cloud, and Azure. 

It also ensures availability, scalability, and compliance with the most stringent data security and privacy requirements. MongoDB Cloud is a unified data platform that includes a global cloud database, search, data lake, mobile, and application services. 

Being a NoSQL tool means that it does not use the usual rows and columns that you associate with relational database management. It is an architecture that is built on collections and documents. The basic unit of data in this database consists of a set of key-value pairs. It allows documents to have different fields and structures. This database uses a document storage format called BSON, which is a binary style of JSON documents. 

The data model that MongoDB follows is a highly elastic one that lets you combine and store data of multivariate types without having to compromise on powerful indexing options, data access, and validation rules. There is no downtime when you want to dynamically modify the schemas. What it means is that you can concentrate more on making your data work harder rather than spending more time preparing the data for the database. 

Here is an example of a document database in MongoDB: 

JSON
  
{ 

_id: name: “Thomson”,
Age: 22,
Address: {{street: “124 church street”,
                  city: “brooklyn”,
                 state: “NY”,
                   zip: “13400”,
                   country: “US”}}
} 


The Architecture of MongoDB NoSQL Database 

Database

In simple words, it can be called the physical container for data. Each of the databases has its own set of files on the file system, with multiple databases existing on a single MongoDB server. 

Collection

A group of database documents can be called a collection. The RDBMS equivalent to a collection is a table. The entire collection exists within a single database. There are no schemas when it comes to collections. Inside the collection, various documents can have varied fields, but mostly, the documents within a collection are meant for the same purpose or to serve the same end goal. 

Document

A set of key-value pairs can be designated as a document. Documents are associated with dynamic schemas. The benefit of having dynamic schemas is that a document in a single collection does not have to possess the same structure or fields. Also, the common fields in a collection document can have varied types of data.  

Important MongoDB Features 

Why Do You Need MongoDB Technology?

This technology overcame one of the biggest pitfalls of traditional database systems, that is, scalability. With the ever-evolving needs of businesses, their database systems also needed to be upgraded. MongoDB has exceptional scalability. It makes it easy to fetch the data and provides continuous and automatic integration. Along with these benefits, there are multiple reasons why you need MongoDB: 

Moreover, businesses are increasingly finding out that MongoDB is ticking all the right boxes when it comes to meeting business requirements. Here is how: 

MongoDB Data Types 

MongoDB supports a wide range of data types, such as: 

Advantages of MongoDB 

1. Distributed Data Platform 

2. Fast and Iterative Development 

3. Flexible Data Model 

4. Reduced TCO (Total Cost of Ownership) 

5. Integrated Feature Set 

6. Long-Term Commitment 

MongoDB cannot support the SQL language for obvious reasons. MongoDB's querying style is dynamic on documents as it is a document-based query language that can be as utilitarian as SQL. MongoDB is easy to scale, and there is no need to convert or map application objects to database objects. It deploys internal memory for providing faster access to data and storing the working set. 

Drawbacks of MongoDB 

Use Cases of MongoDB 

Let’s discuss some use cases of MongoDB in this section. 

Single View

Internet of Things

Real-Time Analytics

Payments

Gaming

Conclusion 

In conclusion, MongoDB is a powerful and flexible database system that offers many advantages over traditional relational databases. Its dynamic schema and ability to handle unstructured data make it ideal for modern applications that require fast and scalable performance. 

We have also seen that MongoDB's architecture is designed for horizontal scalability, allowing it to easily scale out as your application grows. With a thriving community of developers and a wide range of tools and integrations available, MongoDB is a great choice for any project. 

 

 

 

 

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