A querying language plays an important role in performing various operations with the data stored in the database. Before getting into the difference between GraphQL Vs SQL, it is important to have a brief introduction to both these querying languages. SQL is actually a language that is used for making different queries for the data in a relational type of database and it is the standard querying language for such databases.
On the other hand, GraphQL is also a querying language for APIs and not databases. One can use it either with any kind of database or no databases at all. Also, I’ll explain everything that is necessary for you to understand the difference between GraphQL and SQL. I want you to follow along till the end of this article carefully in order to get to know about it in detail.
1. Understanding GraphQL Vs SQL
1.1 What is GraphQL?
GraphQL is a querying language for APIs and not databases. It is developed by Facebook in 2012. It is an open-source querying language. The best thing about GraphQL is that it is not dependent on any database management system. It was built to eliminate the limitations in REST. GraphQL is not SQL or NoSQL, it is basically used to send or receive data between client and server using a minimum number of HTTP requests.
In the backend, GraphQL provides a type system where you can describe a schema for your data, in turn, this gives the front-end consumers of the API, the power to explore and extract data that they need.
1.2 What is SQL?
QL is also known as Structured Query Language, which is used in a DBMS for storing and querying, or managing data. It is used in the relational type of database management systems and it is also a standard language for such types of databases. The best example of RDBMS which is most widely used today is MySql.
So, SQL databases are those that use SQL as a querying language for storing and managing the data.
Note: Both the querying languages GraphQL Vs SQL are totally different from each other in terms of functionality and thus comparing their functionality side by side would not be a good idea. So, I’ll explain the functionality of both of them separately in their own domains so that you can understand them in a much better way.
GraphQL Vs SQL
2. Functioning of SQL
Now in order to understand the functioning of SQL we have to cover a few important concepts first which are really easy to understand and are important to be understood because they play the most important role in the working of SQL(Structured Query Language):
2.1 DDL (Data Definition Language)
DDL is also known as Data Definition Language and it provides a set of definitions for specifying the structure of the databases e.g. tables, etc., and also the access methods for that database. The commands used by DDL are Create, Drop, Rename, and Alter.
2.2 DML (Data Manipulation Language)
DML is also known as Data Manipulation Language and it provides and it allows the user to access data as it is organized by the appropriate data model e.g. the relational model. The commands used by DML are Insert, Update, and Delete.
2.3 How are DDL and DML connected to SQL(Structured Querying Language)?
SQL uses DDL and DML commands in its working, and SQL also uses these commands for defining the relation between structures of a whole skeleton structure of the entire database, deleting relations, and modifying the relations.
3. Functioning of GraphQL
3.1 What is the unique functionality of GraphQL?
First thing first, GraphQL is used for reading and mutating data in APIs. It was actually built to eliminate the limitations in REST API. So, What were the issues or limitations faced by the web developers in using REST APIs?
In the case of REST, data entities live on a bunch of URLs on a server. When a request is received the API responds with the full data payload of that entity. It has two main drawbacks that are explained below:
- The first one is that one may need multiple entities at one time in which case, each request is under-fetching the actual data that we want.
- In the other case, we may want only a subset of a data entity and in which case we have to over-fetch the data from the API.
So, what solution does GraphQL provides for these limitations, and what is its unique functionality? Instead of relying on Multiple URLs, A GraphQL API has a single entry point. Data is queried or fetched by describing it with a syntax that mirrors its return shape in JSON. The front-end developers describe the data they want while the back-end developer writes code to resolve the request. It all happens in a syntax that can work with any programming language.
The best part of using GraphQL is that in the back-end, It provides a type system where you can describe a schema for your data, in turn, this gives the front-end consumers of the API, the power to explore and extract data that they need.
3.2 What are the main functional parts of GraphQL?
GraphQL has three main functional parts that are explained below:
- Query: A query is simply the call we make for the data or for performing any operation with the data. It can make similar queries like SQL in its own way but it is also capable to handle composite fields.
- Resolvers: The resolver tells your GraphQL server where and how to retrieve the data when queried. They can serve other purposes as well as they are not only for this job.
- Schema: It has a typed schema system.
This article takes the readers from the comprehensive definitions of GraphQL and SQL to the detailed list of functionalities of GraphQL and SQL. Now that you have read the article carefully, you must have understood the difference between both of them.
The purpose of discussing all the related concepts is to provide you with a proper understanding of GraphQL and SQL.
Also, let me know in the comment section what do you think about the stuff that I’ve discussed in this article?