What is Mongo DB?

It is a cross-platform document-oriented database system, classified as a NoSQL database, which bridges the gap between key-value systems and traditional RDBMS systems.

MongoDB is a relatively new competitor in the data warehousing circle compared to giants such as Oracle and IBM DB2 but has attracted a lot of attention with its

Thanks to its functionality, MongoDB is the database for Big Data processing.

MongoDB is suitable for situations such as expansion, caching, and areas where high volume traffic plays an important role.

Why is MongoDB so popular?

MongoDB is a NoSQL product and is becoming very popular in the developer community.

Indeed, MongoDB combines perfectly with programming languages ​​such as JavaScript, Ruby, and Python; This perfect mix transmits a high encoding speed.

This functionality, along with its simplicity, has made MongoDB very popular in no time.

How is MongoDB better than traditional RDBMS?

It is the means to efficiently represent different types of data, with colossal read/write scalability and high availability of transactional systems in real-time.

Dominant RDBMS are inadequate to meet this need with their rigid design and low-cost economic sizing solutions.

Therefore Hadoop and NoSQL are complementary in nature and are not competitors.

Flexibility: MongoDB stores data in “Json” documents, where it provides a rich data model that is perfectly suited to the types of native programming language.

And the dynamic schema facilitates the evolution of the data model only with an imposed scheme system, such as an RDBMS.

Power: MongoDB has many features such as secondary indexes, dynamic queries, ranking, complete updates, upgrades, and simple aggregation available in a traditional RDBMS.

This provides functionality similar to RDBMS and also offers additional flexibility and scalability benefits.

Advantages of Mongo DB

Outline: It is perfect for changing the flexible data model.

In MongoDB, it is easy to declare, extend, and modify additional fields in the data model and optional null fields.

Using RDBMS databases, you must primarily run scripts to update the model.

In this case, this can be done through encoding, and no script is required.

The clear structure of a single object: the structure of the model is in “Json,” and the structure is clear rather than derived from a table structure.

No SQL queries or hibernation: the good thing about MongoDB is that the operations are not complex to use (no SQL) and are based on key/value.

You can use easy expression language operators like ‘$ gt,’ ‘$ lt,’ and you can practice with indexes and cursors.

Adjustment: the level of consistency can be chosen based on the value of the data.

Effortless scalability: the scale reads with replica sets and writes with fragmentation (automatic balancing).

Just start another car, and you’re ready to go.

Here, adding more machines to distributes your work.

Automatic sharing allows you to scale the cluster linearly by adding more machines, allowing you to increase capacity without downtime.

No conversion or mapping of application objects to database objects is required.

Quick Access: Uses internal memory to store the work set, allowing faster access to data.

Ease of use: MongoDB focuses on being easy to install, configure, maintain, and use.

For this, MongoDB provides some configuration options and automatically tries to do the right thing.