So many individuals are confused between SQL vs MongoDB differences. They are confused with which one is best for handling data. It is a well-known fact that SQL databases were once important and ruled the world of data technologies, and it has served as a significant source of data storage for more than four decades. SQL databases are most commonly used to access relational databases. Oracle and Microsoft SQL Server dominated the market, but as the Web development industry grew, more people began to use open source databases like MySQL and Postgres. However, RDBMS remained the preferred database management system. Soon enough, data began to rise at an exponential rate, and scalability became a big concern; at that point, MongoDB came to the rescue.
But recently, MongoDB has gained more demand, especially for the scaling feature rendered by the same. The significant difference between SQL Databases and MongoDB is the way they handle data. In SQL databases, data is stored in the form of a traditional 2-dimensional row-column structure, whereas in MongoDB rich data document model is followed, which enables data storage.
Let us see some of the important differences between SQL vs MongoDB…
What Is SQL?
Table of Contents
SQL (Structured Query Language) is a standard database language used to create, maintain and recover relational databases. SQL was started in the 1970s and has become a vital tool since it is important in obtaining, updating, inserting, managing, and changing data. It assists in communicating with relational databases to be able to know the dataset and use it properly. This language is compelling for the database management system. SQL performs various functions in a database system, i.e., insert, update, delete, and create a record in a database system.
SQL Features
SQL is one of the most demanding skills in the current world. A huge amount of data is collected every day, and one has to deal with these databases to make insightful information. Hence, we need to learn SQL. The features of SQL make SQL a most powerful tool. Therefore, here are some of the significant SQL features which make it a strong database programming language:
- High-Performance
- High Availability
- Scalability and Flexibility
- Robust Transactional Support
- High-Security
- Comprehensive Application Development
- Management Ease
- Open Source
What Is MongoDB?
MongoDB is a NoSQL database management system that is free to use. NoSQL databases are a great way to work with big amounts of dispersed data, and they’re a great alternative to traditional relational databases. MongoDB is a database management system that can store and retrieve document-oriented data, and MongoDB can handle an extensive range of data types. It’s one of several non-relational database systems that emerged in the mid-2000s under the NoSQL banner, and it’s typically utilized in big data applications and other processing operations involving data that doesn’t fit neatly into a traditional relational model. Rather than using tables and rows as in relational databases, the MongoDB design comprises collections and documents. Companies can utilize MongoDB for ad-hoc problems, load, indexing, balancing, server-side JavaScript execution, aggregation, and other characteristics.
MongoDB Features
- Each database has collections, which are made up of documents. Each Document is unique, with a distinct amount of fields, and each Document’s size and content may differ from one another.
- The structure of the text corresponds to how programmers create classes and objects in their different programming languages. Developers will frequently claim that their classes have a clear structure with key-value pairs rather than rows and columns.
- The data model possible within MongoDB enables users to express hierarchical relationships, store arrays, and other complicated structures.
- Scalability: Environments of MongoDB are very scalable. Companies worldwide have established clusters, with some running 100+ nodes with millions of documents within the database.
SQL vs MongoDB: Comparison Table
| SQL Database | NoSQL Database (MongoDB) |
| Row-based | Document-based |
| Relational database | Non-relational database |
| Table based | A collection based and key-value pair |
| Supports SQL query language | Supports JSON query language |
| Column based | Field-based |
| Support foreign key | No support for foreign key |
| Includes predefined schema | Includes dynamic schema |
| Vertically scalable – increasing RAM | Horizontally scalable – add more servers |
| Not suitable for hierarchical data storage | Best for hierarchical data storage |
| Support for triggers | No Support for triggers |
Factors that Drive the SQL vs MongoDB Decision
Here are some of the key differences that can be observed in MongoDB vs SQL Databases:
SQL vs MongoDB: Trend
According to the Google trends graph, the SQL database has more demand than MongoDB. It is right to say that a SQL Database is more fitted for businesses and enterprises that deal with structured and Relational data. It is excellent for websites that have high traffic and help a high-performing query engine. Specialized web functions, Data insertions, and quick processing are some of the best features of SQL Databases.
MongoDB vs SQL: Data Storage
The basic role of a database is data storage, and how your data is stored is important when it comes to obtaining and querying. Individual records are saved in MongoDB as documents, which are collections of fields with a dynamic schema. Each collection does not have the same fields, making it more versatile than a relational database management system. Records are kept in rows within a table in SQL Databases, which restricts dynamic classification and storage of hierarchical data. SQL Relational data, on the other hand, can be matched using common properties.
SQL vs MongoDB: Representation, Security, and Convenience
The variation in the way data is described and explained in each makes a meaningful difference. MongoDB stores data in JSON format with key and value pairs for each entity. On the other hand, SQL Databases stores data as a record in a table row. The representation of the storage of a single entity in the databases can be seen as follows:
MongoDB Document
{
name: ”John”,
age: 20,
contact: {
mobile: ”+91-9998888777”,
home_address: ”new street”
}
SQL Databases Record
| Name age | contact-mobile | home-address |
| John 20 | 9998888777 | new street |
While a SQL Database makes data conveniently accessible and classifiable, there are some conditions to storing and processing simultaneously. MongoDB takes a more complicated method to data storage while also allowing for advanced processing. NoSQL does not provide any relations between distinct data types, according to the data representation. While MongoDB is more versatile and ensures a wide range of data availability, a SQL Database follows the ACID (Atomicity, Consistency, Isolation, and Durability) principles and offers superior transactional reliability.
SQL vs MongoDB: Scalability and Replication
One of the most crucial factors for companies and organizations is the scalability and replication functions for broader access. We can’t say one is more scalable than the other unless we use them. SQL Databases expedite Vertical Scaling, that is, Scaling Up. You can increase the RAM, CPU, and SSD sizes to add functionalities to your setup. While this can add some important factors, it cannot change the framework. It helps secure data insertion and uses Slave and Master data replication.
Whereas MongoDB would be more suitable for Horizontal Scaling or Scaling Out. It is, therefore, used by those regularly looking to develop their frameworks, add more servers and increase their storage and set up. This method, known as Sharding, enables dealing with more resilient data and needs more comprehensive informational indexes and system capacities. Sharding is readily facilitated with MongoDB and Replica Sets to increase multiple copies of data for accessibility.
SQL vs MongoDB: Limitations
Limitations Of MongoDB
- MongoDB doesn’t support joins, so you have to update your documents frequently based on how you want to obtain data.
- Since ACID (Atomicity, Consistency, Isolation, and Durability) is not followed rigorously, complex transactions can get difficult.
- Documents have a limit of 16MB.
- MongoDB doesn’t support reserved procedures, so you cannot perform business logic at the database level.
- It has high memory usage because of the key-value sets that can appear in data repetition.
Limitations of MySQL
- Since data is collected in tables, if you have data that doesn’t match any table, you will have to design your database structure again to receive it.
- MySQL becomes less effective when it comes to massive databases due to scaling problems.
- The database has to be shared over multiple servers, which can be hard to maintain.
- MySQL is sensitive to SQL injection attacks.
Conclusion
In this article, we have given an in-depth understanding of SQL vs MongoDB and different factors that make the MongoDB vs SQL Database decision. Companies and organizations of all sizes can use MongoDB to scale-out huge volumes of traffic and data. If you want great pace and certain compliance with the use of unregulated data within a schemaless environment, MongoDB is best.
If you need more information on SQL vs MongoDB difference or any one of them you can take assignment help from us.
Frequently Asked Questions
Which is better MongoDB or SQL?
MongoDB gives faster query processing but with an extended load and system conditions. Without knowing the purpose of use, it is impossible to analyze SQL Databases or NoSQL Databases like MongoDB as better or worse than the other. Several factors drive the MongoDB vs SQL decision.
Is MongoDB different from SQL?
The significant difference between SQL Databases and MongoDB is the way they manage data. In SQL databases, data is collected in the form of the traditional 2-dimensional row-column structure. In MongoDB, a valuable data document model is followed, allowing storage of any data.