How MongoDB help Industry to Grow their Network

Jatin Lodhi
5 min readMay 16, 2021

Welcome Again to Jatin research Work Space 😊 .

Here you get some information about How MongoDB help industry to work fluently and keep on Increase her Network .

( Padna Interesting hai or claps jarur kare !!!!! 😉 )

Start with ….

🤔What Is MongoDB?

MongoDB is a document database with the scalability and flexibility that you want with the querying and indexing that you need

  • The document model maps to the objects in your application code, making data easy to work with
  • Ad hoc queries, indexing, and real time aggregation provide powerful ways to access and analyze your data
  • MongoDB is a distributed database at its core, so high availability, horizontal scaling, and geographic distribution are built in and easy to use
  • MongoDB is free to use. Versions released prior to October 16, 2018 are published under the AGPL. All versions released after October 16, 2018, including patch fixes for prior versions, are published under the Server Side Public License (SSPL) v1.

* The database for modern applications

→ MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era.

*As a programmer, you think in objects. Now your database does too.

→ MongoDB is a document database, which means it stores data in JSON-like documents.

→ This is the most natural way to think about data, and is much more expressive and powerful than the traditional row/column model.

* Makes development easy

→ MongoDB’s document model is simple for developers to learn and use, while still providing all the capabilities needed to meet the most complex requirements at any scale.

→ They provide drivers for 10+ languages, and the community has built dozens more.

Need to run MongoDB?

  • High availability through built-in replication and failover
  • orizontal scalability with native sharding
  • End-to-end security
  • Native document validation and schema exploration with Compass
  • Management tooling for automation, monitoring, and backup
  • Fully elastic database as a service with built-in best practices

Till Here you know What is MongoDB & Why we Need MongoDB !

Now this is the right time to learn some use case …..

MongoDB Use Cases

Here I take only one use case but click on above link you will get all use cases .

Lightweight, low-latency analytics. Integrated into your operational database. In real time.

Most companies use analytics. Many can act on data from months, weeks, or even days ago. But few can respond to changes minute by minute, or second by second. Because:

  • They’re stuck in a mosaic of ETL processes and Excel integrations.
  • They can’t analyze semi-structured, unstructured, and geospatial data.
  • The shape of the data changes faster than their systems can cope with.

With MongoDB, analyze any data in place and in real time. Faster. With less money.

Real-Time Analytics Explained

 * Analytics falls along a spectrum. On one end of the spectrum sit batch analytical applications, which are used for complex, long-running analyses.  * They tend to have slower response times (up to minutes, hours, or days) and lower requirements for availability. *  Examples of batch analytics include Hadoop-based workloads. * On the other end of the spectrum sit real-time analytical applications, which provide lighter-weight analytics very quickly.  * Latency is low (sub-second) and availability requirements are high (e.g., 99.99%). MongoDB is typically used for real-time analytics. 

Example applications include:

Real-Time Analytics is Hard

 * Can’t Stay Ahead. You need to account for many types of data, including unstructured and semi-structured data. And new sources present themselves unpredictably. Relational databases aren’t capable of handling this, which leaves you hamstrung. * Can’t Scale. You need to analyze terabytes or petabytes of data. You need sub-second response times. That’s a lot more than a single server can handle. Relational databases weren’t designed for this.Batch. Batch processes are the right approach for some jobs. But in many cases, you need to analyze rapidly changing, multi-structured data in real time. You don’t have the luxury of lengthy ETL processes to cleanse data for later.

MongoDB Makes It Easy

* Do the Impossible. MongoDB can incorporate any kind of data — any structure, any format, any source — no matter how often it changes. Your analytical engines can be comprehensive and real-time.* Scale Big. MongoDB is built to scale out on commodity hardware, in your data center or in the cloud. And without complex hardware or extra software. This shouldn’t be hard, and with MongoDB, it isn’t.* Real Time. MongoDB can analyze data of any structure directly within the database, giving you results in real time, and without expensive data warehouse loads.

Now learn something about customers success story

In just six months, Forbes migrated its platform to Google Cloud and MongoDB Atlas. Results include:

58% faster build time for new products and fixesAccelerated release cycle by 4xReduced total cost of ownership by 25%28% increase in subscriptions from new newsletters

During the pandemic the cloud infrastructure has also helped the website scale to an extraordinary number of users and helped the team stay nimble, introducing and testing a number of new features.

We’re very glad we moved to the cloud when we did. Shifting quickly to Google Cloud and MongoDB Atlas put us in a position to innovate and thrive even in the most difficult circumstances.

Vadim Supitskiy, Chief Technology Officer at Forbes

That`s all guys here I will give some information about MongoDB .

  • I tried my best to explain as much as possible. I am very confident you will get something useful from this Article
  • Feel free to check out my LinkedIn profile and obviously feel free to comment and give feedback also .






Jatin Lodhi

I am an IT Enthusiast, who is passionate about exploring/learn all the latest technologies from research perspective.