MongoDB Tutorial

History of MongoDB

Dwight Merriman, Eliot Horowitz, and Kevin Ryan launched MongoDB in 2007. At the online advertising firm DoubleClick, all three of the founders were engineers. They wanted to design a database that was more flexible and scalable since they were unsatisfied with the relational databases that DoubleClick was utilising.

Data is stored in documents that resemble JSON objects since MongoDB is a document-oriented database. As a result, data that is not well suited for a relational database can be easily stored and accessed. Additionally, because MongoDB does not demand a rigid schema, the data's structure can vary over time. As a result, adding new data or changing old data is simple and doesn't need making any adjustments.

In 2009, MongoDB launched as an open-source project. It quickly gained popularity and became one of the most popular NoSQL databases. MongoDB Inc., a business that offers MongoDB commercial support and other services, purchased MongoDB in 2013.
 

Why Use MongoDB?

Document-oriented NoSQL database MongoDB is scalable, high-performance, and versatile. Applications that need to store and manage vast amounts of data, especially unstructured data, might consider using it. Since MongoDB does not mandate a rigid schema, the data's organisation may change over time. This makes it simple to modify or add new data without having to alter the database schema. 

Replication and failover are two additional high-availability features that are included with MongoDB. As a result, even if one of the database servers experiences a difficulty, your data will always be accessible.

Features in MongoDB 

It has many distinctive features which make it distinctive from other relational databases, like:

• Document-oriented: the data in MongoDB is stored in a flexible JSON-like document which makes it easier to store and update the data as now we do not need to consider a fixed table schema.
   
• Horizontal scaling: it means that the data can be distributed across multiple servers. If data is distributed then it is easier to process faster.
   
• Indexing: indexing helps improve the query performance and it is inbuilt in Mongodb.
   
• Automatic sharding: it is also one of the features. This feature allows automatic data distribution between the servers. Again distributed data results in faster performance 
   
• Rich query language: MongoDB's query language can handle complex queries and supports a wide range of search criteria.
   
• GridFS: The GridFS feature of MongoDB enables the storage and retrieval of large files such as images and videos.

Setting up MongoDB 

Below is the MongoDB tutorial for the setup in your system.

Download and Install

• go to the official MongoDB site and follow the instruction given there and download it according to your system specs. After the download is done, follow the installation steps.
   

Start Server: 

• to start the MongoDB server, open the terminal in the directory where it is installed and type mongod command to start the server.
   

Connect MongoDB: 

• go to a new terminal and type the mongo command. It will connect to the MongoDB server running on our local machine.
   

Create database: 

• now you can use the option from the menu or type the command <your database>, and replace it with your database name.
   

Create collections: 

• In MongoDB data is stored in collections form and for creating a new collection, type db.createCollection('<your_collection>') command.
   

Data insert: 

• methods like insertOne() or insertMany() to insert documents in the collections according to the need. 

MongoDB's Operation

MongoDB operates in two layers which are the application and data layers, respectively.

Application Layer 

The Application Layer is divided into two parts:
 

• Frontend: This is a User Interface where the user interacts with MongoDB via a web or mobile application.
   
• Backend: This is a server-side which includes a server and mongo shell for interacting with the MongoDB server via queries.
   

Data Layer

These queries are directed towards the MongoDB server, which is present in Data Layer. The server now receives the queries and forwards them to the storage engine. Now, the storage engine takes the responsibility of reading and writing data in files or memory.

Database in MongoDB

In MongoDB, a database is a group of documents. A document is a data-storing object that resembles JSON. A database's documents don't have to follow a set structure and can be of any size or shape. Due to its adaptability, MongoDB may be used to store a range of different types of data.

MongoDB databases are user-friendly for developers and simple to understand and utilise. For MongoDB developers, there are a lot of tools and resources accessible. A high-performance database that can manage a lot of data and queries is MongoDB. This is crucial for applications that require speedy data processing.

Collection in MongoDB

Collections are how MongoDB databases are organised. The term "collection" refers to a set of documents with a common name. Collections can be created, destroyed, and kept on various servers as needed. As a result, MongoDB is a scalable database that can be quickly modified to meet changing requirements. MongoDB databases are an effective means of managing and storing data. They are simple to use, adaptable, and scalable. 

CRUD operations in MongoDB

MongoDB tutorial on how the basics crud operations which are: Create, Read, Update, and Delete work. We will look at each one separately below:
 

• Create: to create a new document, we can use the insertOne() or insertMany() method. To create a single document to a collection using insertOne() method like
   

db.collection.insertOne({ user: "Dhoni" , id: "msd@coding" });

 

• Read: to read data, we can use the find() method. It helps to query and search for the document with the conditions applied, like we want all the documents with a score>75, then use the following command: 
   

db.collection.find({ score: { $gt: 75 } });

 

• Update: just like create, we can update using the updateOne() or updateMany() method. The updateOne() updates a single document which matches the filter we pass, and updateMany() is used to update many documents. One such example is
   

db.collection.updateOne(
  { name: "Dhoni" },
  { $set: { id: “msd@ninja” } }
);

 

• Delete: for deleting we have deleteOne() or deleteMany() methods, the deleteOne() deletes the single document which matches the filter given while the deleteMany() deletes multiple documents. For example
   

db.collection.deleteOne({ name: "Dhoni" });

Indexes in MongoDB

MongoDB indexes are used to perform the queries a lot faster and more efficiently. It is a similar type of index to what we have in a traditional database. It helps to find the data that matches the search parameter more quickly, it does not perform a full scan of the collection when a query is hit, unlike traditional databases. MongoDB has a wide range of index types, including single-key, compound, multikey, text, and geospatial indexes.

Managing indexes in MongoDB

Let’s look into the MongoDB tutorial on how to manage indexes which includes:
 

• Create Indexes: it is used to create an index using the createIndex() method in MongoDB and it takes two arguments which are, an index specification object and an optional object.
   
• Drop Indexes: using it we can drop an index using the dropIndex() method in MongoDB and it takes one argument which is the name of the index to drop.
   
• Compound Indexes: these contain references to multiple collection fields. It helps improve query performance when there are multiple criteria to sort.
   
• Unique Indexes: It ensures that each value is unique across the documents in a collection.

Frequently Asked Questions

Q. What is MongoDB?

A document-oriented database system known as MongoDB uses NoSQL technology. It can handle unstructured or partially organised data since it saves data in a flexible, JSON-like BSON format. Applications include content management, real-time analytics, IoT, web and mobile apps, and more.

Q. What is a MongoDB used for?

A lot of data is stored, retrieved, and managed using MongoDB. Applications like social media platforms, e-commerce websites, and content management systems use it frequently because they need scalability, flexibility, and quick data access.

Q. Is MongoDB better than SQL?

There are distinct uses for MongoDB and SQL. With its flexibility and scalability, MongoDB is useful for managing unstructured data. The selection will depend on the needs of the individual project but SQL databases are suitable for structured data and complicated querying.

Q. Is MongoDB a DBMS?

Yes, MongoDB is a database management system (DBMS). It offers resources and services to effectively organise, store, and retrieve data. Because of its non-tabular, document-oriented data model, it is categorised as a NoSQL DBMS.

Conclusion

Congratulations on finishing this article!! This MongoDB tutorial article covered various topics from the intro to set-up, operations, features, indexes and crud operations. We've also discussed some quality FAQs.

I hope you enjoyed reading this article. Here are some more related articles:
 

• Introduction to MongoDB
• Mongoose for MongoDB
• CRUD Operations in MongoDB
   

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