What Is MongoDB? Introduction, Data Modeling, Terminology & Hierarchy

MongoDB is an open-source, document-oriented, leading NoSQL database for huge data storage volumes. It is completely coded in one of the primitive but relatively very advanced and trustworthy languages, C++. Instead of using traditional relational databases defined on the basic concept of tables and rows, MongoDB relies on the use of documents and collections containing the key-value pairs and making up the platform’s basics. 

It works on multiple platforms with the ability to interact with each other. Some of the notable features of MongoDB include high availability time, best performance, and easy scalability.

Now, to better understand what MongoDB is, we should know all the terminology along with the structure in which MongoDB stores the database.

Database: It acts as a physical container used to collect data. It is stored on a predefined path in the computer system. It contains all valuable data arranged in a specific manner to make it readable by machines. 

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Collection: It acts as an aggregation of documents in MongoDB and corresponds to an RDBMS table. The collection contains documents that can have different fields but are of similar or related purposes.

Document: A set of key-value pairs constitute documents. They work on the dynamic schema, which means that it is not necessary to use the same set or structure in all the documents and handle numerous types of data in a common field. 

_id: It determines the unique part of every document using a 12 bytes hexadecimal number. This consists of four segments-

1. First, four bytes for the timestamp.
2. Next, three bytes for machine ID.
3. Next, two bytes for the process ID of the MongoDB server.
4. The remaining three bytes are just incremental value.

JSON: This is one of the most important features to send and receive data and is known as JavaScript Object Notation. The secret of its popularity is because of its human-readable nature, using plain text format. 

Read: MongoDB Future Scope

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Data Modelling in MongoDB

MongoDB follows a flexible schema. Hence, it is not necessary to define definite data storage structures as in the case of SQL Databases. Certain things are crucial, and you should consider it while modeling data in MongoDB. 

1. Is there a need for such applications that you are developing? Look at the business needs for the application and plan accordingly.
2. Foresee the data retrieval patterns and use the power of indexing to improve your queries. 
3. Frequent inserts, updates, and removals should be verified to maintain the system’s stability and improve the overall MongoDB environment’s efficiency.

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Checkout: Most Common MongoDB Commands

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Terminology and Hierarchy

The first and foremost point includes databases, which include numerous collections. Now, collections are made up of similar documents, and these documents are made up of fields, embedded documents, and primary keys, which are also the default ID provided by MongoDB.

Advantages of MongoDB include-

1. The ability to store data in document-oriented storage that is the JSON styled documents.
2. The ability to distribute data across different machines automatically using an auto-sharding method.
3. MongoDB has an inbuilt rich Query language which supports all major CRUD operations and provides unprecedented Text Search and Aggregation features.
4. Replication of work and high availability is a major advantage of MongoDB, which helps you dedicate your focus to the query you are processing rather than the platform itself. Each replica set member may act in the primary and secondary replica role at any instance of time. The primary replica is the main contact point for the client and users and performs all the operations. The secondary replica maintains a copy of the primary replica data and jumps into action only when the primary replication fails in performing its operations.  
5. Fast-in-place updates keep you updated and market worthy from your comfort of office or homes with regular updates catering to all personal and professional demands.
6. Professional and dedicated support by MongoDB with active forums and developer support because of the open-source culture.
7. Load Balancing: With auto-sharding, we can scale our system horizontally by splitting the available data into multiple MongoDB instances. It can run multiple servers and balance load accordingly in case of failure in any node or server.
8. Indexing: as we know, the indexing is done to increase the search performance of the program. Every field in MongoDB can be indexed using an indexing procedure.  

MongoDB is used in various disciplines such as Big Data, Content Management and Delivery, Mobile, and Social Infrastructure. Management of user and professional data and managing data hubs.

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Also Read: Firebase vs MongoDB

Wrapping up

Companies are looking for new and innovative technologies to work on, and MongoDB is one of them. These new-age skills are very useful to thrive in a competitive environment such as software development, where priorities change every time a new technology is evolved. The hiring in the future will take place, considering these new-age skills.

upGrad has been offering these cutting-edge skills in various domains such as a PG Diploma in Machine Learning and AI, Data Science, & Big Data offered in collaboration with industry partners Flipkart and Indian Institute of Information technology. 

Your future can only be secure if you dedicate your time and effort to pursue your dreams. We at upGrad are here to help you achieve that potential and develop your skills into assets for future companies and organizations by providing real-time inputs and extensive placement support. Make your future secure with us, and don’t let these challenges deprive you of your dreams. 

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