SQL is a widely used programming language that is used to implement databases using tables. Nowadays, various NoSQL databases are also available which display data in other forms than tables. In this article, we will understand the major differences between SQL and NoSQL database languages. We will also learn about both languages and their pros and cons. You need to read the complete article to get a better understanding of the two major database languages (SQL vs NoSQL)
What Is SQL?
SQL is a programming language that helps manage and manipulate relational databases using tables. It stands for Structured Programming Language, which helps users query, manipulate, and change data in a relational database. It provides a standardized way for developers to create, retrieve, update, and delete data in a relational database management system (RDBMS).Â
It allows users to define, control, and modify data to organize and retrieve information. SQL uses commands like Select, alter, insert, update, delete, and many more. It is essential for interacting with databases in various applications.
What is NO SQL?
The No-SQL programming language stands for not only SQL (Structured Query Language). It manages and manipulates both unstructured and structured data. It uses non-relational data structures such as graphs, key-value pairs, documents, JASON, etc. Unlike SQL, it does not use a relational database and is not dependent on fixed schemas.Â
Hence, no SQL is more flexible and adaptable than traditional SQL. They are highly scalable and can distribute data across multiple nodes, which helps them manage big data and real-time applications. It helps developers quickly access and store the data in a database.Â
Which Is Better SQL Or NO-SQL
Choosing one of the two databases totally depends on the user’s choice and their needs and requirements for their project. If you need a quick, accessible, and flexible application database, then NO SQL might be a better option. However, traditional SQL is more beneficial if you need to handle complex queries and transactional data. Both types of databases have their own set of advantages and shortcomings. Hence, there are no hard and fast rules to say which is better in all use cases. Hence, it is important to properly assess your requirements and the nature of the project while choosing between these two databases.
Difference Between SQL And NoSQL
Here in this table, we will understand the significant difference between SQL and NoSQL. Let us now check the table.
| SQL Vs. NoSQL | |
| SQL | NoSQL |
| It stands for Structured Query Language. | It stands for Not Only Structured Query Language. |
| It uses a Relational Database Management System (RDBMS). | It works on a Non-Relational Database Management System. |
| It is a more structured and rigid database. | It is a flexible and adaptive database. |
| It stores the data within the rows and columns of a table. | It can store data in documents and in various forms, such as key-value pairs, documents, graphs, etc. |
| It follows the ACID property. It stands for Atomicity, Consistency, Isolation, and Durability in the transactional management process. | It does not work on the ACID property. |
| It supports various queries, such as JOIN. | It does not support Join and other complicated queries. |
| It uses a Normalized data structure. | It uses a denormalized data structure. |
| It implements vertical scaling to handle large sets of data. | It implements horizontal scaling to handle complex data. |
| It is also known as a database because it displays data in the form of tables. | It is known as a no-table database. |
| They work best in the case of complex queries. | They cannot handle complex queries as well as traditional SQL. |
| They are not suited for hierarchical data storage. | They are suited for hierarchical data storage. |
| MySQL, Oracle, SQL Server, Microsoft SQL Server, PostgreSQL, etc, are some examples of SQL databases. | MongoDB, Amazon DyanamoDB, Neo4j, Couchbase, Redis, HBase, etc, are some examples of NoSQL databases. |
Recommended CourseÂ
- Â Decode DSA with C++
- Full Stack Data Science Pro CourseÂ
- Java For Cloud CourseÂ
- Full Stack Web Development Course
- Data Analytics CourseÂ
Pros And Cons Of Using SQLÂ
Structured Query Langauge is a programming language that is used to manage and modify complex data in the database effectively. Let us now check some of the pros and cons of using SQL in 2023.
Pros of using SQL:
- SQL is a famous database programming language that is widely understood by most developers.
- They effectively handle large and complex databases with their strong queries.
- They are well-oriented and easy to learn.
- They have a simple interface and are still widely used in various top tech companies.
Cons of using SQL
- SQL is a rigid and complex database programming language. It is sometimes hard to crack down on the query logic.Â
- It is less effective as compared to the NoSQL database.
- Debugging SQL queries is often a very complicated process. It also does not provide error messages.Â
- They are not flexible and are hard to implement.
- The syntax of SQL is very similar to other programming languages like R, python, etc. It sometimes gets hard to convert them into functions and scripts.
Important SQL Commands
Let us have a look at some of the significant SQL commands used while manipulating the relational database in the given table.
| Â Â Â Â Â Â Â Â Â Â Â Â Â Important SQL Commands | |
| SQL Command | Description |
| SELECT | Retrieves data from one or more tables. |
| INSERT INTO | Adds new rows into a table. |
| UPDATE | Modifies existing data in a table. |
| DELETE FROM | Removes rows from a table based on a condition. |
| CREATE TABLE | Creates a new table with specified columns and data types. |
| ALTER TABLE | Modifies an existing table (e.g., adding, modifying, or dropping columns). |
| DROP TABLE | Deletes an existing table and all its data. |
| CREATE INDEX | Creates an index on one or more table columns, improving query performance. |
| DROP INDEX | Removes an existing index from a table. |
| JOIN | combines rows from two or more tables based on a related column. |
| UNION | Combines the result sets of two or more SELECT statements. |
| GROUP BY | Group rows that have the same values into aggregated data, like sum or count. |
| HAVING | Filters the results of a GROUP BY clause based on an aggregate property. |
| ORDER BY | Sorts the result set of a query by one or more columns. |
| DISTINCT | Retrieves unique values from a specified column in a table. |
| WHERE | Filters records based on specified conditions. |
| BETWEEN | Select values within a specified range. |
| LIKE | Searches for a specified pattern in a column. |
| IN | Specifies multiple values for a column. |
| NULL | Tests for NULL values in a column. |
PW Skills Provide Various Platform
FREQUENTLY ASKED QUESTIONS (FAQs)
Q1. Which is better SQL or NoSQL, for implementing databases?
Ans: Choosing one of the languages for implementing your database depends on the nature and complexity of your project. NoSQL can be better if you want more flexibility and quicker access times. However, to implement complex queries SQL are often better.
Q2. In which format does SQL display data?
Ans: SQL displays data in the form of tables. However, NoSQL displays data using graphs, key-value pairs, documents, and other formats.
Q3. How many types of databases are there to store the digital data?
Ans: There are two major types of data: Relational databases (SQL) and non-relational databases (NoSQL). They are used to store digital data.
Q4. What are relational databases?
Ans: A Relational database is a type of database that uses a structure based on rows and columns to display data. It organizes and stores data in the form of a table. SQL is an example of a relational database.
Recommended Reads
Data Science Interview Questions and Answers
Data Science Internship ProgramsÂ
