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Introduction MongoDB Architecture – Datanerds.io

Introduction MongoDB Architecture

Introduction To MongoDB Architecture

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MongoDB is an Open source NoSQL Database. As a non-relational database,instead of using tables and rows, MongoDB has a document-oriented data model and makes use of collections and documents.

MongoDB is highly flexible and enables you to combine and store multiple types of data. It also stores and handles larger amounts of data than traditional relational databases. MongoDB uses a document storage format called BSON, which is a binary form of JSON (JavaScript Object Notation) that can accommodate more data types. 

BSON is a serialization format encoding format for JSON mainly used for storing and accessing the documents, whereas JSON is a human-readable standard file format mainly used for transmission of data in the form of key-value attribute pairs. BSON is designed such that it consumes less space, but it is not extremely efficient as JSON.

Cost of MongoDB

MongoDB is cheap and open source. Its implementation is easy and typically uses cheap servers to manage the exploding data and transactions while RDBMS databases are expensive and it uses big servers and storage systems. 

So the storing and processing data cost per gigabyte in the case of MongoDB can be many times lesser than the cost of RDBMS.

Is MongoDB good for structured or unstructured data?

Structured data (also known as relational data) refers to data that fits a predefined data model. It can be easily mapped into designated fields. 

Unstructured data doesn’t have a predefined data model. Therefore, it’s not as easily categorized into the predefined tables and rows of a relational database.

Mongodb can accommodate data having variations in their structure.i.e structured, semi-structured, and unstructured data. MongoDB is a good choice when your data is document-centric and doesn’t fit well into the schema of a relational database, when you need to accommodate massive scale, when you are rapidly prototyping, and a few other use cases.

MongoDB is typically used for flexible data models that need changing. It uses a JSON-like format to store documents. This format directly maps to native objects in most modern programming languages, making it a natural choice for developers, as they don’t need to think about normalizing data. MongoDB can also handle high volume and can scale both vertically or horizontally to accommodate large data loads.

Thus we can imply that if the Structured data is relational data and has a fixed data model then MongoDB is not suitable but it is suitable for all kinds of unstructured data.

MongoDB Use Cases

Industry Based Use Cases:

Finance and E-Commerce

MongoDB is widely used for storing product information and details by finance and e-commerce companies. You can even store the product catalog of your brand in it. MongoDB can also be used to store and model machine-generated data. For this, you can learn the “Storing Log data” document.

Information Technology (IT)

In today’s IT industry, there are a large number of companies who are using MongoDB as a database service for the applications or data storage systems. As per the survey made by Siftery on MongoDB, there are around 4000+ companies confirmed that they are using MongoDB as Database.

HealthCare

MongoDB supports the JSON format. That’s why MongoDB is ready to unify all the patient data, medical records, claims data, policies, and treatment information. For healthcare providers, data interoperability is vital to provide the human-first, value-based patient experience consumers now expect. With interoperability comes the promise of personalized patient experiences and better patient outcomes, driven by the seamless and secure exchange of healthcare data.

Telecommunication

Telcos around the world are using MongoDB to scale quickly, develop new products and services, and increase their speed of innovation. MongoDB’s developer data platform reduces complexity in telecommunications workloads, resulting in more reliable network service for customers.

With continuous uptime and advanced automation, MongoDB’s developer data platform ensures performance, no matter the scale.

Application Based Use Cases:

Content Management System

Content Management systems are a pretty common scenario where MongoDB is used. All the comments on posts on social media are contained in a separate database. In MongoDB, a model has been designed to store such comments and is known as “MetaData and Asset Management”.

Product Data Management

For e-commerce websites and product data management and solutions, one can use MongoDB to store information because it has a flexible schema well suited for the job. One can also manage a product catalog and learn the practices and methods for modeling from the Product Catalog document.

Application-Driven Analytics

MongoDB Atlas makes it easy to bring analytics into your applications. It unifies the core data services needed to bridge the traditional divide between transactional and analytical workloads in an elegant and integrated data architecture.

Internet of Things Databases

The data generated by IoT devices tends to be large in both volume and frequency, placing a unique strain on the underlying data infrastructure. It is also likely to be time series based.

The number of IoT devices available for deployment is also growing, with newer generations of sensors creating more complex and varied data to analyze.

While many databases can be used to store IoT data, some are just better suited to IoT data than others. Due to the polymorphic nature of IoT sensor data, the database you choose needs to support flexible data schemas, make it easy for developers to work with the data, and ensure that your IoT applications are resilient to future changes. By viewing the above mentioned demands it is clearly evident that the most suitable database for this use case is MongoDB.

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