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Sagar Patel

September 16, 2022 190 Views
11 mins read Last Updated September 16, 2022

Quick Summary : MongoDB is an open-source cross-platform NoSQL document-oriented database management program. NoSQL can be utilized as a substitute for traditional relational databases. If you want to work with large sets of distributed data then NoSQL databases may be quite supportive.


MongoDB is an open-source cross-platform NoSQL document-oriented database management program. NoSQL can be utilized as a substitute for traditional relational databases. If you want to work with large sets of distributed data then NoSQL databases may be quite supportive.

It is a tool that can handle document-oriented information, and store as well as retrieve information. It provides the flexibility as well as scalability that you want with the querying and indexing according to your requirement. This tool utilizes JSON-like documents with optional schemas.

It is built by MongoDB Inc. and licensed under the Server-Side Public License (SSPL) which is considered non-free by numerous distributions.

MongoDB is the pioneer of what has known as NoSQL databases, which was created because RDBMS systems based on SQL did not support the scale or rapid software development lifecycles required for making modern applications.

NoSQL is an umbrella term; it contains document-oriented databases like columnar databases, MongoDB, in-memory databases, etc. In this tool, records are stored as documents in compressed BSON files format. The documents can be recovered directly in JSON format, which has many benefits.

MongoDB was first launched on August 27th, 2009. Its first version (Version1) was basic and in version 2 there are lots of features introduced like usable and special indices, sharding, geospatial features, and memory as well as concurrency improvements. Version 3 came with an aggregation framework primarily as an addition to the aging MapReduce framework.

Records will be stored as documents in the MongoDB platform and compressed BSON files. The documents can be recovered directly in JSON format, which has many paybacks like:

  • It is human-readable.
  • It is a normal form to store data.
  • It is human-readable.
  • You can nest JSON to store complicated data objects.
  • Structured, as well as unstructured information, can be stored in a similar document.
  • JSON has a dynamic and flexible schema, so adding fields or leaving a field out is not an issue.
  • Documents map to objects in trendy and famous programming languages.

Most developers find it simple to work with JSON because it is a straightforward as well as a powerful way to store and describe the data. Maybe most significantly, the developer manages the database schema. Developers adjust and modified the database schema as the application develops without the support of a database administrator. When required, MongoDB can organize and control changes to the structure of documents by schema validation.

MongoDB developed Binary JSON format (BSON) to maintain more data types than JSON. This latest format permits faster parsing of the data. Data stored in BSON can be indexed and searched extremely improving performance. MongoDB supports a huge variety of indexing methods, including geospatial, text, decimal as well as partial.

Applications of MongoDB

You must be wondering what is MongoDB used for? MongoDB is broadly utilized across different web applications as the primary data store. One of the most famous web development stacks, the MERN stack employs MongoDB as the data store (MERN Stack full form is MongoDB, ExpressJS, React.js, Node.js).

Some Most Significant Advantages of Mongo DB

MongoDB has become very popular and right now it is one of the trendiest databases in the world because it provides the facility to developers to manage, store as well as retrieve data when making an application with most programming languages. To know whether MongoDB is accurate for you, let’s look at the benefits of MongoDB for developers. You can also check out the top five MongoDB properties.

Here are some advantages of this tool

Advantages of MongoDB

It makes Horizontal Partitioning Easy

This function is utilized when the amount of data you want to store in your database is larger than the size of your drive on the server. Everything linked with the horizontal partitioning is the mark of any NoSQL database. In addition, they can only compete in reliability, response rate, and writing speed.

If we talk about PostgreSQL then it doesn’t contain any built-in horizontal partitioning option. There are several third-party solutions. The same thing is simply implemented in MongoDB, there are whole many articles about it. The Replication mechanisms along with the sharding function make it perfect for this tool.

Furthermore, the balancer may automatically select in which shard to store which documents as well as it also can set the rules regarding some fields or the set of ones.

It’s schemaless 

This one is major payback for MongoDB. If you are working for a startup with an unclear business model and you know there are lots of changes that are going to happen in its pre-market stage, provide NoSQL (MongoDB in particular) a shot.

The good thing is that in MongoDB there is no requirement to make tables, run migrations, modify their schemas, and think about data types but be alert about that. The assistance here is that it makes it simpler for you to make new tables as well as add or delete fields. When you used this tool then It’s so simple that you just insert a line like a field: text, type: String in the model as well as when you put some information, the fresh element in your database is going to have that field.

If you insert the data without ORM, you don’t even require any lines, just put whatever you would like to. But there’s also the disadvantage. You cannot be extremely sure if in a specific document you have a particular field (Document is a bunch of MongoDB entries) Especially, if you did not have a field called ‘text’ initially then added some entries and then you have to add this field and some more entries, you are not going to get the similar field for the old entries. It will affect that such a field already exists for the old entries and just return the null value.

High Speed As Well As Higher Availability

MongoDB is a document-based database solution. It has attributes like grid and replication. Their feature permits a boost in data availability. With the use of indexing, it is also simple to access documents. Its performance is 100 times quicker than other relational databases as well as offers high.

Performance Levels

MongoDB stores the majority of the data in the RAM. It permits a faster performance while executing queries. It receives the data directly from the RAM than the hard disk as well as the returns come back more rapidly. It is essential to have a system with RAM and correct indexes to improve performance levels.

It has tremendous data aggregation

SQL is very complicated and everybody is familiar with its difficulties of it, so I’m not going to denote the stones at it but the way of getting data in MongoDB deserves praiseful. The MongoDB tool includes the map-reduce function, creating the documents on-the-fly, grouping according to numerous conditions, generating random documents as well as sorting. So here is everything that you can get from an SQL database along with saving it by the pipeline system and with extra legible syntax.

Simplicity

MongoDB provides an uncomplicated query syntax that is much simpler to grasp than SQL. It also gives an expressive query language that users find useful during development.

It includes Simple index types

The index names in MongoDB are understandable as well as we do not face any restrictions while inserting them into action. For example, if in PostgreSQL you have a gist index in one field and a b-tree index in another when you form an inquiry so at that time only one of those indexes will be utilized. There are fewer such surprises in MongoDB.

It’s Designed for Denormalization

In MongoDB, we can store data according to our choice. In SQL databases you always will have to be attentive to the data management (Note: you must use your brain and not contain the word ‘always’ as the rule of thumb), so that even if each table is normalized as well as the queries are badly-written so they can still recover the data. If the layout of the data or the place where it’s stored is not suitable in the MongoDB tool for you so you can shift it or duplicate it to the essential place beyond shame because this database is schemaless. Particularly, you might have a similar field with similar data, but in unusual collections. Or maybe two fields in one set and on top of that one more field which is the grouping of the first two. But you shouldn’t neglect it. Without any limitations, if you multiply fields in the documents, it will become more and more complex for a developer to understand data entities.

Why Use MongoDB?

In this section, we are going to discuss the use of the MongoDB tool. MongoDB is made on a scale-out structural design that has become trendy with developers of all kinds for building scalable applications with evolving data schemas.

As a document database, MongoDB makes it simpler to store unstructured or structured data for the developers. It contains a JSON-like format to store documents. This layout directly maps to native objects in the latest programming languages and makes it a likely choice for developers because with it they do not need to think about normalizing data. MongoDB can also manage high volume as well as can scale both horizontally and vertically to accommodate large data loads.

MongoDB was developed for people who are creating business and internet applications that need to grow rapidly and scale elegantly. Organizations and development teams of all sizes utilize MongoDB for a wide variety of reasons. MongoDB is a general-purpose database system utilized in different ways to support applications in many different organizations (e.g., gaming, telecommunications, finances, healthcare as well as retail).

MongoDB has found a home in various businesses and functions because, in the field of software development and data management, it solves long-standing and difficult problems. Typical use cases for MongoDB include:

Supporting hybrid as well as multi-cloud applications

MongoDB can be utilized and run on a desktop, an enormous cluster of computers in a data center, or in a public cloud, either as installed software or through MongoDB Atlas, a database is like a service product. If you have applications that want to run wherever they make sense so MongoDB will support that app configuration now and in the future.

Providing data in high-performance applications

MongoDB’s scale-out structure can support vast numbers of transactions on humongous databases. MongoDB is scalable out of the box. It is not like other databases that either cannot support such scale or can some tools only do so with massive amounts of engineering and additional components, MongoDB has a clear path to reliability because of the way it was built.

Combining huge amounts of diverse data

If you are carrying together hundreds of data sources then the flexibility, as well as the power of the document model, can make a single integrated view in ways that other databases cannot. MongoDB has done very well in bringing such projects to life when methods using other databases have failed.

Describing complex data structures that evolve

Document databases permit the embedding of documents to illustrate nested structures as well as simply accept variations in data in generations of documents. Specific data formats like geospatial are proficiently supported. This results in a flexible repository that doesn’t break or require to be modified every time something changes.

Supporting collaboration as well as Agile Development

Document databases add developers in charge of the data. It becomes friendly for the developers because data becomes like code in the system. This is extremely different from making developers use a strange system that needs an expert. Document databases also permit the growth of the structure of the data as needed for better understanding. Governance and collaboration can permit one team to manage one part of a document as well as another team to manage another part.

Final Words

MongoDB is not a golden platform. There might be some unforeseen hidden issues and one of them is that it does not disable slow queries from itself, so if you will close them manually at that time they will still run.

I do not want to encourage all of you to move from SQL databases to MongoDB, but if are confused and want to select a new project so you can go with MongoDB. MongoDB is a general-purpose database platform that can offer many advantages to your application development processes.

It can support you to make applications that are more future-proof with its scaling abilities as well as flexible schema. It gives the best developer experience with drivers for trendy major programming languages and a big community of users.

It is also accessible on any of the major cloud providers. Groovy Web can assist you in Web Application Development in all possible ways to make things effective for you.


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Written by: Sagar Patel

Sagar Patel is the CTO and Co-founder of Groovy Web. He was involved in the telecommunications & Automation industry during his early career. Still, due to his attitude toward learning anything new and mastering it, he now works as a CTO for Groovy Web. Through their business mindset and logical approach, they have taken their company to the next level; His responsibilities now include all aspects of the business. Among them are finance, process design, and development.


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