Case Study of MongoDB

Hello Friends,

I have completed task which is based on MongoDB Use case.

I would like to thank Mr. Vimal Daga Sir and Linux World for support& motivating .

Task Description: Create one use-case blog or case-study on how industries are using MongoDB?

What is MongoDB:

MongoDB is an open-source document-oriented database. It is used to store a larger amount of data and also allows you to work with that data. MongoDB is not based on the table-like relational database structure but provides an altogether different mechanism for storage and retrieval of data, that’s why known as NoSQL database. Here, the term ‘NoSQL’ means ‘non-relational’. The format of storage is called BSON ( similar to JSON format).

How it works?

Now, we will see how actually thing happens behind the scene. As we know that MongoDB is a database server and the data is stored in these databases. Or in other words, MongoDB environment gives you a server that you can start and then create multiple databases on it using MongoDB.

Because of its NoSQL database, the data is stored in the collections and documents. Hence the database, collection, and documents are related to each other as shown below:

Features of MongoDB –

·       Schema-less Database: It is the great feature provided by the MongoDB. A Schema-less database means one collection can hold different types of documents in it. Or in other words, in the MongoDB database, a single collection can hold multiple documents and these documents may consist of the different numbers of fields, content, and size. It is not necessary that the one document is similar to another document like in the relational databases. Due to this cool feature, MongoDB provides great flexibility to databases.

·       Document Oriented: In MongoDB, all the data stored in the documents instead of tables like in RDBMS. In these documents, the data is stored in fields(key-value pair) instead of rows and columns which make the data much more flexible in comparison to RDBMS. And each document contains its unique object id.

·       Indexing: In MongoDB database, every field in the documents is indexed with primary and secondary indices this makes easier and takes less time to get or search data from the pool of the data. If the data is not indexed, then database search each document with the specified query which takes lots of time and not so efficient.

·       Scalabiltiy: MongoDB provides horizontal scalability with the help of sharding. Sharding means to distribute data on multiple servers, here a large amount of data is partitioned into data chunks using the shard key, and these data chunks are evenly distributed across shards that reside across many physical servers. It will also add new machines to a running database.

·       Replication: MongoDB provides high availability and redundancy with the help of replication, it creates multiple copies of the data and sends these copies to a different server so that if one server fails, then the data is retrieved from another server.

·       Aggregation: It allows to perform operations on the grouped data and get a single result or computed result. It is similar to the SQL GROUPBY clause. It provides three different aggregations i.e, aggregation pipeline, map-reduce function, and single-purpose aggregation methods

·       High Performance: The performance of MongoDB is very high and data persistence as compared to another database due to its features like scalability, indexing, replication, etc.

Advantages of MongoDB:

·       It is a schema-less NoSQL database. You need not to design the schema of the database when you are working with MongoDB.

·       It does not support join operation.

·       It provides great flexibility to the fields in the documents.

·       It contains heterogeneous data.

·       It provides high performance, availability, scalability.

·       It supports Geospatial efficiently.

·       It is a document oriented database and the data is stored in BSON documents.

·       It also supports multiple document ACID transition(string from MongoDB 4.0).

·       It does not require any SQL injection.

·       It is easily integrated with Big Data Hadoop

Disadvantages of MongoDB:

·       It uses high memory for data storage.

·       You are not allowed to store more than 16MB data in the documents.

·       The nesting of data in BSON is also limited you are not allowed to nest data more than 100 levels.

Use Case of Expedia:

Problem: Expedia, an American travel company, is a travel aggregator website. As the travel fares vary from day to day, these websites are left with very little inventory.

This use case of MongoDB focuses on storing and processing big data to improve customer experience.

Travelers often plan well ahead of their travel and go through a number of options. Most of the time, they tend to forget their previous searches, and it leads to confusion amongst travelers.

Solution: To solve this problem, Expedia came up with a solution called Scratchpad.

It is powered with MongoDB. Scratchpad allows you to customize your trip package as per your needs, and it automates the entire note-taking process. It also allows you to search on the laptop and automatically saves the info on your mobile/tablet.

With Scratchpad, you also get the lowest price deals, based on previous searches.

A system needs to handle a lot of data and process a huge amount of information to automate, filter, and personalize to deliver the exact content.

MongoDB helps Expedia to deliver just that. As MongoDB is a non-relational database, it becomes easy to customize all of the information pretty quickly and without any hassle.

The key reason behind choosing MongoDB was its speed and ease of scalability as you can store the values in a single view. It would have been too long and a bit slow to process all of the information and deliver the results in real-time.

Use Case of Bosch:

Problem: One of the interesting use cases of MongoDB involves Bosch. Internet of Things (IoT) has transformed the way businesses operate, and Bosch, one of the technology leaders, is not lagging behind.

Bosch has invested a lot on smart power tools and advanced telematics. The key driver to these projects has been the Internet of things.

IoT doesn’t just deal with connected devices, but it also specializes in giving real-time insights to improve the processes.

Solution: MongoDB has helped Bosch to deliver the IoT-powered apps to its consumers.

As the IoT market is inflating, Bosch plans to implement IoT in most of its services, and MongoDB is accelerating this process for Bosch by giving them an advantage with the scalability and high level of availability.

It would have been difficult for Bosch to execute and implement the IoT platforms with the relational database systems.

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