---
canonical_url: https://www.scaler.com/topics/difference-between-sql-and-nosql/
title: Difference between SQL and NoSQL | SQL VS NoSQL - Scaler Topics
description: This article by Scaler Topics talks about the difference between SQL and NoSQL databases. It discusses how data is stored and when to use each of them. Read to know more.
author: Rishabh Mahajan
category: SQL
amphtml: https://www.scaler.com/topics/difference-between-sql-and-nosql/amp/
publish_date: 2022-01-24
---

:::section{.abstract}

When considering database options, the primary decision revolves around choosing between relational (SQL) or non-relational (NoSQL) databases. Each option has its strengths and weaknesses, necessitating careful consideration based on specific user requirements. Understanding the difference between SQL and NoSQL is crucial for informed decision-making in selecting the appropriate database solution.

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:::section{.main}
## Key Differences between NoSQL and SQL

There are various parameters on which we can compare the differences between SQL and NoSQL.

| Parameter | SQL Databases | NoSQL Databases |
|:---------------------------:|:-------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------:|
| **Definition** | SQL Stands for Structure Query language. It is used in relation databases. | NoSql stands for Non Sql, and it is used in non-relational databases. |
| **Data Model** | SQL databases use a relational model, organizing data into tables with predefined schemas. | NoSQL databases employ various data models, such as key-value pairs, document stores, wide-column stores, or graph databases. |
| **Database Structure** | They are in the form of tables that contain rows and columns, and have fixed logical schema design | They contain collections, and inside every collection, there is a document that contains the data of a single entry |
| **Scalability** | SQL databases support `vertical scaling`, In vertical scaling, we improve the single server by increasing RAM, SSD or CPU. | we can do `horizontal scaling` in NoSQL databases because they support distributed computing. |
| **Language** | We use standard structured query language in SQL databases. | NoSQL databases have dynamic schemas and no fixed query language to work with them. |
**Properties** |In the world of SQL databases, the **ACID** acronym is used heavily. |As NoSQL databases are used with distributed systems, they need to follow the **CAP** principle. |
|**Support & deployment** | You get great support from all the vendors of **SQL**. There are so many consultants available to help with the deployment of SQL. |For **NoSQL**, you need to rely on community support. |
|**Example**|Eg. MongoDB, CouchDB, Neo4j, RavenDB, etc.|Eg. MongoDB, CouchDB, Neo4j, RavenDB, etc.|

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:::section{.main}

## What is SQL

SQL is pronounced as **“S-Q-L”** or **“See-Quel”** and stands for **`Structured Query Language`**. We use SQL in a Relational Database Management System called RDBMS. **RDBMS** is software used to `store, manage, query,` and `fetch data` in a relational database.

In Relational databases, we store data in the form of **tables, rows** and **columns**, and some of the tables are connected with each other in some relation. Consider the following image: We have different tables, and one table represents one entity. We add a new record as a new row in the respective table. This traditional system of managing data is known as an RDBMS.


Various examples of SQL databases, such as **MySQL, MariaDB, Oracle, and PostgreSQL **, are used to manage databases.

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:::section{.main}

## What is NoSQL

NoSQL stands for **“Not Only SQL”** or **“Non SQL”**. It is **used in non-relational databases**. As the name suggests, data is not formed in form tables in NoSQL databases.
*`Non-relational databases`* are different from traditional relational databases. Here, we store data in the form document, which is a key value pair data structure. Consider the following image where the data is stored in the object.

{
name: "sue",
age : 26
status : "A"
groups : ["news", "sports"]
}

In NoSQL, we have collections, which are nothing but the grouping of these documents. If we compare the documents and collections with RDBMS, then the collections are analogous to the table, and the documents are analogous to the rows. In the above example, the object in which data is stored is known as JSON(Javascript object notation).

Consider the following image. We have the Employee_Info database, which has two collections, Employee and Projects, each containing a number of documents.


In the above example, we have stored data using collections; each collection has multiple documents. One document stands for one entry. There is no specific structure for NoSQL databases; they can have a variety of structures.
There are four major types of NoSql databases:

- Document databases
- Key value databases
- Graph databases
- Wide-column stores

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:::section{.main}

## When To Use: SQL vs NoSQL

### SQL
- SQL is the most accessible for working with relational databases.
- SQL is sound when you want to perform complex queries using join.
- SQL shines if you want to perform quick data storage and retrieval operations.
- If your application doesn’t require huge scaling, you can choose SQL.
- SQL is a must when ACID properties are needed in transactions.

### NoSQL

- The first apparent reason to use NoSQL is if you are designing a distributed system.
- NoSQL is a must if you want a hierarchical storage structure instead of a table-like structure.
- NoSQL allows you to create dynamic structures and add features as you go.
- When there is no need for ACID properties during application, you can consider NoSQL.
- When you want to do horizontal scaling and create a vast computer system in the future.

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:::section{.summary}

## Conclusion
* In this article, we saw the difference between sql and nosql.
* SQL databases use a structured schema, while NoSQL databases offer flexibility with schema-less data structures.
* SQL databases ensure data integrity through ACID properties.
* NoSQL databases prioritize scalability and performance, often sacrificing strict consistency for higher throughput.
* SQL databases excel in handling relationships between data through joins and foreign keys.
* NoSQL databases are designed for distributed architectures, offering horizontal scalability without expensive hardware upgrades.

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