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What is MongoDB?

What is MongoDB?


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.

Check out this insightful video on ‘MongoDB?’:

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 so much 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

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

‘Users love MongoDB because it offers the fastest time to value compared to any other DBMS technology.’ – Eliot Horowitz, Developer of MongoDB

Enrich your knowledge in what is MongoDB Sharding and the process of creating it.

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Dwight Merriman, Eliot Horowitz, and Kevin Ryan created MongoDB in 2007. To provide a solution for the problems of scalability and agility that they were facing at DoubleClick, they decided to develop a database. That’s when MongoDB came into existence.

  • MongoDB was first developed by 10gen Software in 2007 as part of a proposed platform as a service solution.
  • The firm switched to an open-source development approach in 2009, with commercial support and additional services available.
  • MongoDB Inc. replaced 10gen as the company’s name in 2013.
  • It became a publicly traded business on October 20, 2017, when it was listed on NASDAQ as MDB with an IPO price of $24 per share.
  • It announced a partnership with Alibaba Cloud on October 30, 2019, to provide a MongoDB-as-a-Service solution to its clients. Customers can access BABA’s managed services from any of the company’s worldwide data centers.

How Does MongoDB Work?

Being a NoSQL tool means that it does not use the usual rows and columns that you so much 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

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

Go through this blog to acquire knowledge about Redis Vs MongoDB!

The Architecture of MongoDB NoSQL Database

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 for serving 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.

Find out more about MongoDB in this comprehensive MongoDB Tutorial now!

Important MongoDB Features

  • Queries: It supports ad-hoc queries and document-based queries.
  • Index Support: Any field in the document can be indexed.
  • Replication: It supports Master-Slave replication. MongoDB uses the native applications to maintain multiple copies of data. Preventing database downtime is one of the replica set’s features as it has a self-healing shard.
  • Multiple Servers: The database can run over multiple servers. Data is duplicated to foolproof the system in the case of hardware failure.
  • Auto-sharding: This process distributes data across multiple physical partitions called shards. Due to sharding, MongoDB has an automatic load balancing feature.
  • MapReduce: It supports MapReduce and flexible aggregation tools.
  • Failure Handling: In MongoDB, it’s easy to cope with cases of failures. Huge numbers of replicas give out increased protection and data availability against database downtimes like rack failures, multiple machine failures, and data center failures, or even network partitions.
  • GridFS: Without complicating your stack, any size of files can be stored. GridFS feature divides files into smaller parts and stores them as separate documents.
  • Schema-less Database: It is a schema-less database written in C++.
  • Document-oriented Storage: It uses the BSON format which is a JSON-like format.
  • Procedures: MongoDB JavaScript works well as the database uses the language instead of procedures.

Also, check out the blog on MongoDB Projects.

Why do you need MongoDB technology?

This technology overcame one of the biggest pitfalls of the 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:

  • No downtime while the application is being scaled
  • Performs in-memory processing
  • Text search
  • Graph processing
  • Global replication
  • Economical

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

  • MongoDB provides the right mix of technology and data for competitive advantage.
  • It is most suited for mission-critical applications since it considerably reduces risks.
  • It increasingly accelerated the time to value (TTV) and lowered the total cost of ownership.
  • It builds applications that are just not possible with traditional relational databases.

Checkout the difference between Elasticsearch vs MongoDB

Check out this insightful video on ‘How to Learn MongoDB?’

MongoDB Data Types

​​MongoDB supports a wide range of datatypes, such as:

  • String − Must be UTF-8 valid
  • Integer − Stores a numerical value of 32 bit or 64 bit depending upon the server
  • Boolean − Stores true/ false value
  • Double − Stores floating point values
  • Min/Max keys − Compares a value against the lowest and highest BSON elements
  • Arrays − Stores arrays, lists, or multiple values into one key
  • Date − Stores the current date or time in UNIX format
  • Timestamp − Useful for keeping a record of the modifications or additions to a document
  • Object − Used for embedded documents
  • Object ID − Stores the ID of a document
  • Binary data − For storing binary data
  • Null − Stores a null value
  • Symbol − Used identically to a string but mainly for languages that have specific symbol types
  • Code − For storing JavaScript code into the document
  • Regular expression − Stores regular expression

Advantages of MongoDB

You ought to know why technocrats project MongoDB as one of the best NoSQL databases.

Find out the six aspects through which you can realize the benefits of MongoDB:


1. Distributed Data Platform

  • Throughout geographically distributed data centers and cloud regions, MongoDB can be run ensuring new levels of availability and scalability.
  • With no downtime and without changing your application, MongoDB scales elastically in terms of data volume and throughput.
  • The technology gives you enough flexibility across various data centers with good consistency.

2. Fast and Iterative Development

  • Changing business requirements will no longer affect successful project delivery in your enterprise.
  • A flexible data model with dynamic schema, and powerful GUI and command-line tools, makes it fast for developers to build and evolve applications.
  • Automated provisioning enables continuous integration and delivery for productive operations.
  • Static relational schemas and complex operations of RDBMS are now something from the past.

3. Flexible Data Model

  • MongoDB stores data in flexible JSON-like documents, which makes data persistence and combining easy.
  • The objects in your application code are mapped to the document model, due to which working with data becomes easy.
  • Needless to say, schema governance controls, data access, complex aggregations, and rich indexing functionality are not compromised in any way.
  • Without downtime, one can modify the schema dynamically.
  • Due to this flexibility, a developer needs to worry less about data manipulation.

4. Reduced TCO (Total Cost of Ownership)

  • Application developers can do their job way better when MongoDB is used.
  • The operations team also can perform their job well, thanks to the Atlas Cloud service.
  • Costs are significantly lowered as MongoDB runs on commodity hardware.
  • The technology gives out on-demand, pay-as-you-go pricing with annual subscriptions, along with 24/7 global support.

5. Integrated Feature Set

  • One can get a variety of real-time applications because of analytics and data visualization, event-driven streaming data pipelines, text, and geospatial search, graph processing, in-memory performance.
  • For RDBMS to accomplish this, they require additional complex technologies, along with separate integration requirements.

6. Long-term Commitment

  • You would be staggered to know about the development of this technology.
  • It has garnered over 30 million downloads, 4,900 customers, and over 1,000 partners.
  • If you include this technology in your firm, then you can be sure that your investment is in the right place.

MongoDB cannot support the SQL language for obvious reasons. MongoDB 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 the internal memory for providing faster access to data and storing the working set.


‘The cost of managing traditional databases is high. Mistakes made during routine maintenance are responsible for 80 percent of application downtime.’ – Dev Ittycheria, President and CEO of MongoDB Inc.

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Drawbacks of MongoDB

We have discussed the advantages of MongoDB. Now, let’s take a look at some of its drawbacks:

  • It uses high memory for data storage
  • Document size has a limit
  • Less flexibility with querying
  • There is no transaction support
  • While it’s fast evolving, there is lack of updated information

Use Cases of MongoDB

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

Single view:

  • You can quickly and easily create a single view of anything with MongoDB even with a smaller budget.
  • A single view application collects data from many sources and stores it in a central repository to provide a single view of anything.
  • MongoDB makes single views simple with its document model, Dynamic Schemas, and expressive query language.
  • MongoDB’s single view is widely used in financial services, government, high-tech, and retail.

Internet of Things:

  • MongoDB can assist you in quickly capturing the most value from the Internet of Things.
  • MongoDB offers Data Ingestion with high-speed and it provides real-time analytics which is helpful for IoT. Companies like Bosch and Thermofisher rely on MongoDB for IoT.

Real-time analytics:

  • Analyze any data faster, anywhere, in real-time, with MongoDB.
  • It can store any type of data, regardless of its structure, format, or source, and regardless of how frequently it changes.
  • MongoDB is designed to run on commodity hardware, whether in your data center or the cloud without the need for any additional gear or software.
  • MongoDB can analyze data of any structure right in the database, providing real-time results without the need for costly data warehouse loads.
  • The city of Chicago analyses data from 30+ various agencies using MongoDB to better comprehend and respond to situations, including bus whereabouts, 911 calls, and even tweets.


  • To outperform the competition, payment platforms must provide a flexible, real-time, and enhanced customer experience.
  • Industry leaders use MongoDB as the backbone of their always-on, always secure, always available payments infrastructure, from consumer brands to businesses.
  • Companies like nets icon solution use payment services of MongoDB.


  • Video games have always relied heavily on data. Data is essential for making games function better.
  • It assists in various aspects from player profiles to telemetry, matching to scoreboards.
  • The flexible document data format in MongoDB allows you to easily estimate the capacity of a player.
  • Add additional features to player profile items like achievements, progression-based unlocks, in-game money, new gear classes, and more.
  • At the data layer, use enterprise-grade security measures to keep your players safe.
  • Companies like Sega and Faceit use gaming from MongoDB.

What is MongoDB Atlas?

MongoDB Atlas is a multi-cloud database, an easy-to-use service model. It is developed by the same developer teams that build the MongoDB open-source database. It handles the databases, and makes deployment easy by providing effective, scalable, and flexible solutions that you need to build a distributed database management system. It offers fully managed MongoDB deployment across AWS, GCP, and Azure. Any combination of AWS, Azure, and GCP can be used to design Multi-Cloud, Multi-Region & replicas for workload isolation MongoDB deployments in Atlas.

Features of MongoDB Atlas

  • It automatically backs up the data and provides point-in-time recovery features.
  • It is a pay-as-you-go pricing model, which makes it a cost-effective solution.
  • MongoDB Atlas serves applications to a global user base deployment.
  • It provides an isolated environment, and RBAC mechanisms to secure authentication access and protect sensitive data. 

MongoDB Atlas on AWS, Azure, and Google Cloud Providers: Database Deployment

Steps to be followed:

  1. To deploy the database, select the database types. MongoDB Atlas can deploy two types of cloud database clusters and serverless instances.
  2. Select the cloud provider (AWS, Azure, and GCP) and high-availability distributed data across regions.
  3. Design custom Multi-Cloud, Multi-Region & replicas for workload isolation MongoDB deployments in Atlas. Set up the nodes in the MongoDB deployment:
  • Cloud providers
  • Geographic regions
  • Workload priorities
  • Replication configurations

MongoDB Atlas on AWS, Azure, and Google Cloud Providers: Authenticate the Database Access:

Steps to be followed:

  1. Configure the IP access list entries
  2. Configure database user management. Atlas provides authentication for database users: Passwords, X.509 certificates, AWS IAM, LDAP, and OIDC.
  3. Configure the network peering connection, whereas Atlas supports network peering connections for dedicated clusters hosted on AWS, GCP, and Azure and on multi-cloud sharded clusters.

MongoDB Atlas on AWS, Azure, and Google Cloud Providers: Strategically Fine-Tuning the Database

Steps to be followed:

  1. Configure custom Alerts. When a condition triggers an alert, then resolve the Alerts.
  2. Analyze the Index, slow queries, and Schema Suggestions.
  3. Define Atlas archives criteria depending on the type of collection you want to archive: Standard Collection and Time Series Collection.

Comparison Between MongoDB and other Databases

In this section, we are going to compare MongoDB with different databases like RDBMS, MySQL, and Cassandra.  

MongoDB vs RDBMS:

You can directly compare the MongoDB NoSQL with the RDBMS and map the varied terminologies in the two systems: The RDBMS table is a MongoDB collection, the column is a field, the tuple/row is a document, and the table join is an embedded document. The typical schema of a relational database shows the number of tables and the relationship between the tables, but MongoDB does not follow the concept of relationship.

Go through the following table to understand how exactly an expert NoSQL database like MongoDB differs from RDBMS. This blog has elucidated nine different comparisons between the two.

Document-oriented and non-relational databaseRelational database
Field-basedColumn based
Collection based and key-value pairTable based
Gives JavaScript client for queryingDoesn’t give JavaScript for querying
Relatively easy to setupComparatively not that easy to setup
Unaffected by SQL injectionQuite vulnerable to SQL injection
Has dynamic schema and ideal for hierarchical data storageHas predefined schema and not good for hierarchical data storage
100 times faster and horizontally scalable through shardingBy increasing RAM, vertical scaling can happen

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MongoDB vs MySQL

The following table explains the differences between MongoDB and MySQL

The query language is javascriptThe query language is a structured query language
It represents data as JSON documentsIt represents data in tables and rows.
Defining the schema is not requiredDefining tables and columns is required
It does not support JOINIt supports JOIN
MongoDB was built with high availability and scalability in mind and offers replication and sharding out of the box.Although the MySQL idea does not allow for effective replication and sharding, it does let users retrieve related data via joins, which reduces duplication.
Because of its design, MongoDB is less of an attack.It has a risk of SQL injection attacks.

To have a detailed comparison between Firebase and MongoDB, check out MongoDB vs SQL!

MongoDB vs Cassandra

Here is the comparison between MongoDB and Cassandra.

It is a database system that is free and open-source, cross-platform, document-oriented.It is a database system that is open-source, distributed, and decentralized
It can be written in C, C++, and JavaScriptIt can be written in only Java
It is document-basedIt is column based
It has triggersIt does not have triggers
It has secondary indexesIt has restricted secondary indexes

Learn more tips on Best Practices for MongoDB in this insightful tutorial.

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Frequently Used Commands in MongoDB

Database Creation

  • MongoDB doesn’t have any methods to create a database. It automatically creates a database when you save values into the defined collection for the first time. The following command will create a database named ‘database_name’ if it doesn’t exist. If it does exist, then it will be selected.
  • Command: Use Database_name

Dropping Databases

  • The following command is used to drop a database, along with its associated files. This command acts on the current database.
  • Command: db.dropDatabase()

Creating a Collection

  • MongoDB uses the following command to create a collection. Normally, this is not required as MongoDB automatically creates collections when some documents are inserted.
  • Command: db.createCollection(name, options)
  • Name: The string type which specifies the name of the collection to be created
  • Options: The document type specifies the memory size and the indexing of the collection. It is an optional parameter.

Showing Collections

  • When MongoDB runs the following command, it will display all the collections in the server.
  • Command: In shell you can type: db.getCollectionNames()

$in Operator

  • The $in operator selects those documents where the value of a field is equal to the value in the specified array. To use the $in expression, use the following prototype:
  • Command: { field: { $in: [<value1>, <value2>, … <valueN> ] } }


  • Often you need only specific parts of the database rather than the whole database. Find() method displays all fields of a document. You need to set a list of fields with value 1 or 0. 1 is used to show the field and 0 is used to hide it. This ensures that only those fields with value 1 are selected. Among MongoDB query examples, there is one that defines projection as the following query.
  • Command: db.COLLECTION_NAME.find({},{KEY:1})

Date Operator

  • This command is used to denote time.
  • Command:
    Date() – It returns the current date as a string.
    New Date() – It returns the current date as a date object.

$not Operator

  • $not does a logical NOT operation on the specified <operator-expression> and selects only those documents that don’t match the <operator-expression>. This includes documents that do not contain the field.
  • Command: { field: { $not: { <operator-expression> } } }

Delete Commands

  • Following are commands which explain MongoDB’s delete capabilities.
  • Commands:
    collection.remove() – It deletes a single document that matches a filter. db.collection.deleteOne() – It deletes up to only a single document even if the command selects more than one document.
    db.collection.deletemany() – It deletes all the documents that match the specified filter.

Where Command

  • To pass either a string that has a JavaScript expression or a full JavaScript function to the query system, the following operator can be used.
  • Command: $where

The forEach Command

  • The javaScript function is applied to each document from the cursor while iterating the cursor.
  • Command: cursor.forEach(function)

If you have any query related to MongoDB, kindly post it on our Community!

Where can you use the MongoDB NoSQL database?

The MongoDB NoSQL database can be extensively used for Big Data and Hadoop applications for working with humongous amounts of NoSQL data that is a major portion of Big Data. MongoDB and SQL are all database systems, but what sets them apart is their efficiency in today’s world. MongoDB can also be successfully deployed for social media and mobile applications for parsing all streaming information which is in the unstructured format. Content management and delivery also see extensive use for the MongoDB NoSQL database. Other domains are user data management and data hubs.

Get familiar with top MongoDB Interview Questions to get a head start in your career!

Who is using MongoDB?

MongoDB is used by a significant number of organizations in the IT sector today as a database service for applications or data storage systems. According to a survey conducted by Siftery on MongoDB, over 4000 companies have verified that they use MongoDB as a database. The following are some of the organizations that are using MongoDB.

  • IBMUber.
  • Lyft.
  • Intercom
  • Citrix
  • Delivery Hero.
  • Twitter
  • InVision
  • HTC
  • T-Mobile
  • LaunchDarkly.
  • Sony
  • Stack.
  • Castlight Health
  • Accenture
  • Zendesk

Discover MongoDB Partner Ecosystem Catalog

MongoDB partner: Confluent Cloud

Utilize the full capability of streaming data pipelines with MongoDB.

MongoDB partner: Databricks Lakehouse Platform

Develop AI-enhanced applications with a simplified and highly scalable architecture.

MongoDB partner: Together AI 

Together, AI and Atlas Vector Search enable end-to-end retrieval and augmented generation, which makes them one of the most useful stacks.

MongoDB partner: Vercel

Create an application rapidly and with high scalability with MongoDB Atlas and Vercel. 

MongoDB partner: Amazon CodeWhisperer

Making the coding experience seamless, and accelerating the developer innovation experience.

MongoDB partner: LangChain

Make the development process easy and deploy genAI applications with MongoDB and LangChain.

MongoDB partner: LlamaIndex

Deploying LlamaIndex with MongoDB accelerates the GenAI app development process.

MongoDB partner: Mongoose

Mongoose provides features in data modeling, model validation, schema enforcement, and general data manipulation with MongoDB.

MongoDB partner: Slack

Integrating tools in MongoDB Atlas with Slack to receive Atlas alerts in the Slack channels. It is one of the most used stacks.

MongoDB partner: HashiCorp

HashiCorp offers provisioning, managing, and controlling Atlas configurations as code on any cloud provider.

How to install MongoDB on Windows 10

Now, let’s see the installation process of MongoDB on Windows 10. Follow the steps mentioned below:

Step 1: Go to the MongoDB official page. Then click on the software on your top left. 

Step 2: From the software, click on the community server option.

Step 3: Then you will see this MongoDB Community Server which is 4.4.6 version and msi package. Click on the download button to Download the software.

Step 4: After completing of downloading,  open the downloaded .msi file. You will see something like the below image. Click on Next to continue.

Step 5: Then Accept the license agreement and click on Next.

Step 6: Then you have to choose the setup type. Click on the Complete option

Step 7: Then you will be asked to specify optional settings to configure MongoDB as a service. To specify options follow the steps below:

  • Install MongoDB as a service 
  • Run service as a Network service user.

Then click on Next to continue.

Step 8: Next, you will see an option to install MongoDB compass which is optional. You can keep it selected if you want or deselect it if you don’t. Click on Next.

Step 9: From here you can install the software. Click on Install to start the installation process.

The installation process starts.

Step 10: Finally, the installation process is completed. Click on Finish.

This is the installation process of MongoDB. Now let’s talk about the scope of MongoDB NoSQL.  

What is the scope of MongoDB NoSQL?

Some of the biggest companies on earth are successfully deploying Mongo, with over half of the Fortune 100 companies being customers of this incredible NoSQL database system. It has a very vibrant ecosystem with over 100 partners and huge investor interest who are pouring money into the technology, relentlessly.

One of the biggest insurance companies on earth MetLife is extensively using MongoDB for its customer service applications; the online classifieds search portal, Craigslist is deeply involved in archiving its data using MongoDB. One of the most hailed brands in the media industry, The New York Times is using MongoDB for its photo submissions and the application that is deployed for form-building. Finally, the extent of MongoDB dominance can be gauged by the fact that the world’s premier scientific endeavor spearheaded by the CERN physics laboratory is extensively using MongoDB for its data aggregation and data discovery applications.

Who is the right audience for learning MongoDB technology?

  • Software Developers, Architects, and Administrators
  • Database and Analytics Professionals
  • System Administrators and Research Professionals

How will this technology help you in your career growth?

  • MongoDB is the most widely used NoSQL database application –InfoWorld
  • A MongoDB Database Administrator in the United States can earn up to $129,000 per annum – Indeed
  • Hadoop and NoSQL markets are expected to reach $3.3 billion within the next two years – Wikibon

MongoDB is a very useful NoSQL database that is being used by some of the biggest corporations in the world. Due to some of the most powerful features of MongoDB, it offers a never-before-seen set of features to enterprises in order to parse all their unstructured data. Due to this, professionals who are qualified and certified in working with the basics and the advanced levels of MongoDB tools can expect to see their careers soar at a tremendous pace without any doubt. Due to its versatile and scalable nature, MongoDB can be used for datasets like social media, videos, and so on. MongoDB clients and users won’t feel a need for any other kind of database.

MongoDB Course from Intellipaat will provide you with the right set of skills to work with NoSQL databases in the best companies.

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About the Author

Technical Reseach Analyst - Data Engineering

Abhijit is a Technical Research Analyst specializing in Deep Learning. He holds a degree in Computer Science with a focus on Data Science. Being proficient in Python, Scala, C++, Dart, and R, he is passionate about new-age technologies. Abhijit crafts insightful analyses and impactful content, bridging the gap between cutting-edge research and practical applications.