We will discuss the difference between the MS SQL server and the MONGO DB server here.
MongoDB
MongoDB Inc. developed MongoDB on 11 February 2009, and MS SQL was Developed by Microsoft Corporation on April 24, 1989. MONGO DB is written in C++, Go, JavaScript, and Python languages, and MS SQL server is written in C and C++. MONGO DB and Microsoft SQL Server are offered both free and paid versions. MONGO DB provides a free and open-source Community Edition, which is useful for application development.
Microsoft SQL Server
Microsoft SQL Server provides a free version called SQL Server Express with limited features which suitable for small applications and learning purposes. For handling large-scale applications, the Enterprise Edition of MongoDB is there with a cloud-based service called MongoDB Atlas. MS SQL provides paid versions with different designs called Standard Edition, Enterprise Edition, Developer Edition, and Web Edition.eBay, LinkedIn, Adobe with cloud-based services and applications, and The New York Times are famous Mongo DB Companies. Bank of America for transaction and financial data management, Uber, and Amazon are real-time examples for Microsoft SQL Server users.
Microsoft SQL is a relational database, and data is organized in a table structure, also called a structured database. SQL is a Structured Query Language that can be used in different database platforms, including MySQL, Oracle, and Microsoft SQL Server. I also manage structured data, like inventory data, customer information, and financial records.
NoSQL MongoDB is called an unstructured or semi-structured database with no relationship between data. It is helpful to handle flexible data like user-generated content, social media data, and Content Management Systems (CMS).
![MongoDB vs MS SQL Server]()
Data Model
Data Models in MS SQL and MONGO DB differ from the structure example.
MS SQL-Relational Model
The relational data model was followed in the Structured database. Data is saved in fixed schemas with rows and columns in table format. Relationships between tables using foreign keys and allowing for joins with tables.
Example
| ID |
UserName |
Password |
| 1 |
aaa |
xxxxxxxxxx |
| 2 |
bbb |
xxxxxxxxxx |
MongoDB-Document Model
Documents-orientated database with JSON-like (BSON) - format and different fields in a collection stored in the database.
Example
{
"_id": "1",
"name": "ss",
"email": "[email protected]",
"items": [
{ "itemId": "101", "amount": 50 },
{ "itemId": "102", "amount": 75 }
]
}
Schema
SQL data is handled with tables, rows, and columns, a kind of fixed set of Structure. Foreign keys and complex joins are also possible. The data type of each column in thetable has specific data types like INT, VARCHAR, DATE, etc.
Example
Table: Employees
- ID (INT, Primary Key)
- FirstName (VARCHAR)
- LastName (VARCHAR)
- DepartmentID (INT, Foreign Key)
Table: Department
- ID (INT, Primary Key)
- Name (VARCHAR)
MONGO DB is a Schema database in BSON format saved as a document; there are No joins between each document. Only links inside the documents also handle nested kinds of documents.
Example
Collection: Employees
{
"ID": 1,
"FirstName": "John",
"LastName": "Doe",
"Department": {
"ID": 101,
"Name": "Sales"
}
}
Performance
SQL is the Vertical scalability of complex queries and transactions with properly indexing data structure.
Mongo DB is horizontal scaling and large volumes of data because document-oriented storage also allows the distribution of data across multiple servers.
Querying
SQL Query Example
SELECT * FROM Employees WHERE Department = 'Sales';
MongoDB Query Example
db.Employees.find({ Department: 'Sales' });