What is MongoDB with Example? SQL vs MongoDB Shortcuts - The Easy Way

What is MongoDB with Example? SQL vs MongoDB
What is MongoDB? SQL vs MongoDB

Introduction: What is MongoDB?

MongoDB is a document-oriented database management system (NoSQL) developed by 10gen. It was designed to handle big data sets and provide high performance. MongoDB uses JSON documents to store data. A JSON document is similar to a relational table row except that each field is not constrained to have a name and value pair. Instead, a JSON document may have any number of fields.


 {_id: ObjectId("5effaa5662679b5af2c59989"),
 email: “email@example.com”,
 name: {given: “Jessica”, family: “Xaio”},
 age: 32,
 addresses: [{label: “house”,
              street: “101 Elverm Street”,
              city: “Springfield”,
              state: “CA”,
              zip: “90000”,
              country: “US”},
             {label: “mom”,
              street: “5515 Main Street”,
              city: “Jonestown”,
              province: “Ontario”,
              country: “CA”}]

A note about the name field: it contains both the given and family name components. The addresses field stores an array of addresses. Each address can contain different fields, so we can easily store different kinds of information.

More specifically, it’s an open-source database program that has several built-in features including versioning, automatic replication, and clustering.

These things allow for fast failure recovery and increased overall system stability, which is important when you have a highly-active application serving millions of people.

Another advantage of MongoDB is its flexibility. It is very useful in many different ways depending upon one's needs. For example, if you only need to store a small amount of information then using something like a simple DB would be much more efficient than running an entire MySQL or SQL server instance.

If you want better performance though, then you should consider upgrading to the full version of MongoDB and installing the driver from here. : https://www.mongolab.com/downloads.html

This will give you access to the full capabilities of this platform. If desired, you could also run multiple MongoDB instances on one machine to create replica sets. To ensure high reliability, these replicas can be placed across various machines.

You could also install MongoDB on another popular cloud service, such as Amazon's EC2. Then you can use load balancers to make sure all the traffic hits every node in your cluster.

The above steps explained how to set up and use a single copy of MongoDB. If you wanted to build a reliable and scalable solution then you must think about implementing a proper architecture.

What is the difference between SQL vs MongoDB?

MongoDB is a document-oriented database management system (DBMS) designed to scale horizontally across commodity hardware using a free open-source software license. It was originally developed at 10gen Inc., a startup company based in New York City, and released in 2008. MongoDB is written in C++ and uses JSON documents stored in BSON format.

SQL is a declarative programming language used to query and manipulate data held in relational databases. It consists of a set of commands that tell the database how to retrieve, store, delete, and update information. SQL is often used to interact with a MySQL server.

So what’s the difference?

The biggest difference between SQL and Mongo is that MongoDB stores data in JSON documents while SQL stores data in tables. In addition, MongoDB doesn't require a schema to define the structure of data.

In SQL, you need to create a table before inserting any data. You then have to specify the columns and their types. If you want to add a column later, you'll have to drop the table and recreate it.

In MongoDB, you don't need to create a table first. Instead, you simply insert data into collections. Collections are groups of related data that share similar characteristics. For example, if you're storing customer records, you might group them under a collection called customers.

You can use the same code to access both SQL and MongoDB databases. However, you'll need different drivers depending on whether you're working with SQL or MongoDB.

Using the MongoDB Shell

The MongoDB shell provides an easy way to navigate, inspect, and manipulate document data. To start the shell, type mongo followed by the name of the database you wish to access. For example, if you wanted to view the documents in the test database, you would type the mongo test command.

Here are a few quick shell examples:

List Databases
 > show dbs;
admin    0.000GB
config   0.000GB
local    0.000GB
my_database  0.004GB

List Collections
 > use my_database;
> show collections;

Count Documents in a Collection
 > use my_database;
> db.users.count()

Find the First Document in a Collection
 > db.users.findOne()
    "_id": ObjectId("5ce45d7606444f199acfba1e"),
    "name": {given: "Alex", family: "Smith"},
    "email": "email@example.com"
    "age": 27

Find a Document by ID
 > db.users.findOne({_id: ObjectId("5ce45d7606444f199acfba1e")})
    "_id": ObjectId("5ce45d7606444f199acfba1e"),
    "name": {given: "Alex", family: "Smith"},
    "email": "email@example.com",
    "age": 27

Why use MongoDB

If you have data that needs to be saved quickly, accessed rapidly, and is easy to maintain
MongoDB has several features that make it a very powerful tool :
  • It can support multiple users
  • There are incremental backup cycles
  • Its collections consist of databases that are similar to tables in other systems

Install MongoDB

MongoDB is one of the most popular databases available, and for good reason! It’s purpose-built for scale-out across your infrastructure has a flexible schema, and is highly interactive and real-time.

It may seem like you need more than just to install MongoDB to start using it, but this powerful database takes a bit of work to set up. Grab a drink, read through the next few sections, and get started installing and setting up the application files needed for your server.

You can do that by searching our documentation section for “MongoDB” or reading their official getting started guide here.

Also, since this is free open-source software, have patience with yourself and others who are new to the platform. There are many helpful resources available online as well as at your local computer library.

Create a database

Databases are like folders in the cloud, where different things go depending on what you need to keep track of. You can create as many databases as you want, which is great because you don’t have to limit yourself to using only one.

Each database has its own set of tables, columns, records, or whatever term you use for the individual units that make up your data. Each of these objects has properties that define them, similar to how there are differences between folder attributes.

When working with files, we know that there are certain aspects of each file that define it, such as filename, extension, size, etc. When working with datasets, this information is also applicable; however, instead of files, data is the unit of transfer.

Furthermore, while users may be able to access and edit any of the data in their library, not all programs support creating sets, making it easier to manage who can get access to what.

There are several types of databases, including personal (aka “collaborative”), team, group, and organization versions of the same program.

This help improves efficiency by letting people share documents and information, either through sharing a link OR allowing multiple individuals to work on the same document at once.

Create a collection

With MongoDB, you create collections to store documents (each document is called a record). Collections help you organize your data into an accessible format and give you control over what goes in each collection.

Each collection has its own set of keys (fields) that define how elements are ordered and indexed.

Control over where data is stored is essential for any useful application since all apps need to access data. By storing data in a database with ACID properties, you can use this app to modify data without fearing it failing due to some other process trying to access it at the same time.

ACID stands for atomic, consistent, isolated, and durable. Atomic means that every part of the operation completes successfully; consistently means that the results are the same every time; isolated means that changes only affect parts of the system independent of one another; and durable allows past state transitions to be retained even if something fails later.

For example, consider a situation where two users are both editing text files online independently. If there was no interconnection between their browsers, either user could save their file right away, but they would lose their work because there would be duplicate entries.

By using transactions, both users will have their edits saved at the same moment, kind of like clicking “commit” twice. Because things were written together, they are considered simultaneous.

If DBMSs cannot guarantee these services, then they are not

Insert one document

Document-oriented databases, such as MongoDB, focus on the efficient storage of documents. Each document may contain several fields that store information. Documents are stored in a directory called “collection”, which provides for easy replication and reduced hardware dependence.

A standard database requires you to organize your data into tables within the application or layer you are working in. To get access to this data, you need to use APIs and functions to pull out the information you want.

In comparison, document-oriented databases provide a simple way to store information in a structured format (i.e., documents). A document is simply a group of easily understood pieces of information like an article will be. There are no rows or columns involved.

When we talk about documents, the computer handles them as unstructured objects. You can create links between items contained in a document using special properties of the text representation used for strings.

You can also identify groups of related documents by creating collections. More often than not, these are known as folders. In MongoDB, there are only two types of collections: empty collections and models. Models are what hold all of your documents and their contents.

The model itself is just a folder with an index.json file inside it. The index.json defines some metadata associated with the model, including which database to use and where to find it.

This makes finding information much simpler because you don 

Update a document

The next thing you will learn about MongoDB is how to update a document. You will either insert or replace an object in a collection.

To perform an INSERT, use the $addObjectID operator with any new fields that you want to add to your documents. To do a REPLACE, use the $setoperator with the field name as described below.

Let’s look at an example. We are going to start with an empty document and we will then tell the database to ADD A FIELD named ‘x’ with a value of 15.

After doing this, our document looks like this.

We can now run another command to UPDATE THIS DOCUMENT using the _id field which points to the id for this specific document. Here is what it should look like after running the second command.


Here, we are looking at an article that has two sections. One section is titled “Article stats (count)” and one is called “You must read this…”

There is no record in the docs folder with the title “Article stats” but there is a record with the title “You Must Read This…”. So, let us get some data from these records.

I am going to open 2 different terminals

Read a document

MongoDB is referred to as a ‘document database’ since its documents are the basis of the entire system. A collection can be thought of as an organized folder structure, where each article or page that goes into the database lives in its separate file and belongs to a different collection. Each collection has its independent SQL interface, manages its schema (data model), allows for multiple databases, and provides rules for data validation.

Data is represented in a JSON-like format known as BSON. This makes queries and manipulation of records within a collection efficient and quick.

Schemas are defined concerning a collection. When no scope is specified, everything under the root _ directory falls under the default global scope. Scopes can have functions, packages, variables, and constants.

MongoDB supports two types of schemas via plugins. There are standalone schemas that cannot collide with other internal software using native methods, and external schemas that use their APIs. Using external schemas enables greater flexibility in how you design your data structures.

Plugins let you add new fields to collections without doing major reworks because they work separately from the original DB. In addition, every operation performs slowly due to the additional steps needed to implement the plugin. Data migration becomes even more difficult when there are several versions of each app sharing one database.

Delete a document

The way you delete a record in mongo is by doing either an update or a find and then using one of the methods to remove that document.

Both will take downtime, where members of your team can be interrupted when they are working on updating the database. Furthermore, these actions are time-consuming and have a substantial amount of overhead.

The second method uses threads instead; it takes less time but still has a delay while waiting for everyone on the team to re-sync their changes.

A much better option is to use version control within your team. This could be something as simple as git or mercurial. These programs allow teams to work offline and online independently, any member of the team can make updates at any time.

There are many other features including security with this set up which I won’t go into here. Briefly though, when a change is made outside of the revision control system, all will again break down and sync up the revisions before merging them back into the repository.

This helps with consistency throughout the project and prevents gaps in data integrity.

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