While the majority of users in the world today are converting to MongoDB, many people still favour using a conventional relational database. Why should we pick MongoDB, we'll discuss here. It has advantages and disadvantages of its own, just like every coin has two sides.

Are you prepared to investigate the benefits of learning MongoDB now?

Why MongoDB?

Due to the fact that it is a NoSQL database, there are numerous reasons to learn MongoDB. These factors laid the groundwork for MongoDB's widespread appeal.

These are a some of the explanations for MongoDB's appeal.

• Aggregation Framework
• BSON Format
• Sharding
• Ad-hoc Query
• Capped Collection
• Indexing
• File Storage
• Replication
• MongoDB Management Service (MMS)

Aggregation framework

MongoDB makes it highly effective for us to use. Data processing in batches and data aggregation procedures are both possible with MapReduce. MapReduce is nothing more than a technique that uses parallel and distributed algorithms running on clusters to process and provide results from massive datasets.

It itself consists of two sets of operations, Map() and Reduce ().

Map(): This function sorts a dataset after performing actions like filtering the data.
After map(), reduce() performs the task of summarizing all the data.

BSON format

It is a storage format similar to JSON. Binary JSON is known as BSON. When storing documents in collections, MongoDB utilises a binary-encoded serialisation of JSON-like documents called BSON. Data types like date and binary (which JSON does not support) can be added.

Here, _id is used as a primary key in BSON format. Since _id is being used as a primary key, it has a special value called an ObjectId that is produced either by the application driver or the MongoDB service.

An example of the BSON format is provided below to help you understand it better:

{
"_id": ObjectId("12e6789f4b01d67d71da3211"),
"title": "Key features Of MongoDB",
"comments": [
...
]
}

Utilizing the BSON format also makes it possible to index and map document properties internally. It boosts MongoDB's read/write throughput because it is made to be faster and more efficient in terms of size.

Sharding

Scaling is the main issue with any web or mobile application. MongoDB has implemented the sharding capability to help with this. It is a technique for distributing data among numerous computers. With sharding, horizontal scalability is offered.

It takes several shards to complete the difficult task. Each shard serves as a separate database and stores a portion of the data. When all the shards are combined, a single logical database is created. Query routers are in charge of operations over here.

Ad hoc queries

Typically, we don?t know the exact queries we?ll be running when designing a database?s structure. Ad-hoc queries are those that weren?t anticipated while the database was being organised.

As a result, MongoDB offers ad-hoc query capabilities, which is what distinguishes it in this situation. Performance is enhanced as a result of real-time updates to ad-hoc queries.

Schema-Less

One collection in MongoDB contains a variety of documents. Since it lacks a schema, it is capable of having many different fields, contents, and sizes than other documents in the same collection. Because of this, MongoDB handles databases with flexibility.

Capped Collections

Because its collections have defined sizes, MongoDB supports capped collections. The insertion order is maintained. Once the cap is reached, it begins to behave like a circular line.

Limiting our capped collection to 2MB, for instance

db.createCollection(?logs?, {capped: true, size: 2097152})

Indexing

Indexes are being constructed to enhance search performance. Any field in a MongoDB document can be indexed, either as a main or secondary field.

The database engine can effectively resolve queries as a result.

File Storage

Additionally, MongoDB can be utilised as a file storage system, preventing load imbalance and data replication. The Grid File System, which is integrated into drivers that store files, is used to execute this purpose.

Replication

Replication is the method that MongoDB employs for redundancy. Data is distributed across numerous machines via this feature. It is possible for it to have primary nodes and one or more replica sets. Replication essentially prepares for unexpected events.

The secondary node takes over as the primary node for the instance when the primary node is unavailable for some reason. This expedites maintenance and streamlines business processes.

MongoDB Management Service (MMS)

We can follow our databases or machines and, if necessary, backup our data thanks to MongoDB's extremely potent MMS feature. In order to manage the deployment, it also monitors hardware metrics.

It offers a tool called custom alert, thanks to which we can find problems before they have an impact on our MongoDB instance.

Advantages of MongoDB

Disadvantages of MongoDB

Summary

Therefore, after reading it, you may understand why we should use it and discover 10 reasons to learn about MongoDB in 2023.