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Table of contents
1.
Introduction
2.
What is an SQL Database?
3.
What is a NoSQL Database?
4.
Key difference between SQL and NoSQL
5.
When To Use: SQL vs NoSQL
5.1.
When to Use SQL
5.2.
When to Use NoSQL
6.
Importance of SQL
7.
Importance of NoSQL
8.
Frequently Asked Questions
8.1.
Q. Why is NoSQL better than SQL?
8.2.
Q. Is NoSQL faster than SQL?
8.3.
Q. How do you choose between SQL and NoSQL?
8.4.
Q. Why is NoSQL used for big data?
9.
Conclusion
Last Updated: Mar 27, 2024
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Difference between SQL and NoSQL

Author Tashmit
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Introduction

SQL databases are relational and use a structured query language, while NoSQL databases are non-relational and use a variety of data models. SQL databases are vertically scalable, while NoSQL databases are horizontally scalable. The choice between SQL and NoSQL databases depends on the specific requirements of your application. 

Difference Between SQL and NoSQL

In this article, we will briefly study the difference between SQL and NoSQL databases, their examples and their advantages.

What is an SQL Database?

SQL (Structured Query Language) is a programming language that manages and manipulates relational databases. It allows users to store, retrieve, update, and delete data from databases.

Some basic and most common Sql commands are:

  1. SELECT: It retrieves data from one or more tables in the database.
     
  2. INSERT INTO: It is used to add new data to a table.
     
  3. UPDATE: It is used to modify existing data in a table.
     
  4. DELETE: It is used to delete data from a table.
     
  5. CREATE TABLE: It creates a new table in the database.
     
  6. ALTER TABLE: It is used to modify the structure of an existing table.
     
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What is a NoSQL Database?

NoSQL (Not only SQL) is a non-relational Database management system that allows storing and retrieving unstructured or semi-structured data. Unlike traditional SQL databases, NoSQL databases do not use tables, rows, and columns to store data. Instead, they use a variety of data models such as key-value, document, column-family, or graph.

Here are some common NoSQL databases and their data models:

  1. MongoDB: It is a document-oriented database that stores data in JSON-like documents.
     
  2. Cassandra: A column-family database stores data in columns rather than rows.
     
  3. Redis: It is a key-value database that stores data as key-value pairs.
     
  4. Neo4j: A graph database stores data with nodes, relationships, and properties.


NoSQL databases are designed to handle large volumes of data, provide high availability and scalability, and can be used in distributed environments. They are popular in modern web and mobile applications that require fast and flexible data storage and retrieval.

Key difference between SQL and NoSQL

Below is the comparison table to show the difference between SQL and NoSQL.

Features SQL NoSQL
Data Model It is a relational data model. It represents data as tables with rows and columns. It consists of key-value, document, column-family, and graph
Scalability It is vertically scalable. We can increase the resources of a single server or machine to handle more load. It is horizontally scalable. We have to add more machines or servers to distribute the workload.
Querying The querying is done by using Structured Query Language (SQL). Queries are API-based and often lack support for complex querying
Flexibility SQL is less flexible for unstructured data NoSQL is more flexible for unstructured or semi-structured data
Transactions It supports transactions and is widely used It has limited support and often requires custom implementation
Schema SQL has a strict schema, pre-defined table structure NoSQL has a flexible schema, dynamic and self-describing
Examples MySQL, Oracle, Microsoft SQL Server MongoDB, Cassandra, Redis, Neo4j

Also see,  Checkpoint in DBMS

When To Use: SQL vs NoSQL

Let's discuss one by one when to use SQL and NoSQL.

When to Use SQL

  • Structured Data: When your data is well-organized and follows a fixed schema.
     
  • Complex Queries: For complex queries involving multiple tables and relationships.
     
  • ACID Transactions: When data consistency and integrity are critical (e.g., financial systems).
     
  • Scalability: When vertical scaling (adding more resources to a single server) is sufficient for your needs.
     
  • Reliability: For well-established and mature database systems.
     

When to Use NoSQL

  • Unstructured or Semi-Structured Data: When your data is flexible and doesn't fit neatly into tables.
     
  • High Read/Write Throughput: For applications requiring rapid data ingestion and retrieval.
     
  • Scalability: When you need horizontal scaling (adding more servers) to handle massive data and traffic growth.
     
  • Speed: When you need low-latency access to data, especially in real-time applications.
     
  • Flexibility: For agile development, the data schema may evolve frequently.

Importance of SQL

Below points show the importance of SQL.

  1. It can handle large volumes of data efficiently.
     
  2. It is easy to use for querying and managing data.
     
  3. SQL is standardized across various relational database systems.
     
  4. It is flexible and supports various applications and use cases.
     
  5. SQL provides robust features for data analysis, reporting, and visualization.
     
  6. It is a valuable tool for business intelligence and decision-making.

Importance of NoSQL

Below points shows the importance of NoSQL.

  1. NoSQL databases are designed to scale horizontally. This helps to increase the performance, as more nodes are added to a cluster.
     
  2. NoSQL databases can handle unstructured or semi-structured data, making them suitable for a variety of use cases.
     
  3. NoSQL databases are often faster than traditional SQL databases because they are optimized for specific data models and do not require complex queries.
     

Must Read SQL Clauses And  Recursive Relationship in DBMS 

Frequently Asked Questions

Q. Why is NoSQL better than SQL?

NoSQL databases are better than SQL in scenarios where you need flexibility with unstructured data, high scalability, and rapid data access. They excel in handling big data, real-time applications, and distributed systems.

Q. Is NoSQL faster than SQL?

Not necessarily. The speed of NoSQL vs. SQL depends on the specific use case and how well the database is optimized. Both can be fast but excel in different scenarios.

Q. How do you choose between SQL and NoSQL?

Choose SQL when data is structured, relationships are complex, and ACID transactions are crucial. Opt for NoSQL for unstructured data, high scalability, and rapid, flexible development in dynamic environments.

Q. Why is NoSQL used for big data?

NoSQL is used for big data because it's designed to handle massive volumes of unstructured or semi-structured data efficiently, offering scalability, flexibility, and low-latency access, which are crucial for big data applications.

Conclusion

In this article, we studied a brief about SQL and NoSQL and the difference between SQL and NoSQL. SQL databases are relational and use a structured query language, while NoSQL databases are non-relational and use a variety of data models. You can refer the SQL article for better understanding of the topic. Must read Pros and Cons of Using SQL vs NoSQL Databases.

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