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GraphQL vs SQL: Differences, Similarities, and Why to Use Them

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Querying data from databases has only been possible thanks to query languages such as SQL, GraphQL, FQL, HTSQL, Oracle PL/SQL, RDQL, etc. There are a handful of query languages available for the developer to make data requests from databases.

The exchange of data has permitted the sharing of information between different devices, clients, and servers through APIs (Application Programming Interfaces).

However, as more of these languages evolved, we realized that different query languages are suited for different purposes. This is evident as SQL as a query language is only suited and has been the de facto query language since the '70s for relational databases. GraphQL on the other hand is a query language for APIs.

In this article, you will be introduced to what SQL is, what GraphQL is, their differences and their similarities, the advantage of one over the other, and finally, you will read about some reasons why you should use one over the other in your next project.

What is SQL?

SQL stands for Structured Query Language. It is used to build, store, and process data in relational or tabular databases. Information stored in relational databases is in tabular form, with rows and columns representing different data attributes and the various relationships between the data values.

SQL is one of the most popular query languages of choice.

What is GraphQL?

According to the official documentation of GraphQL;

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.

GraphQL is an open-source data query and manipulation language for APIs (Application Programming Interfaces) that lives between a client application and a server. It is used as an API endpoint, that allows you as a developer to fetch exactly the information you need with the least number of requests to the server.

Why Use GraphQL in Your Application?

  • GraphQL is a great choice for applications that need you to make multiple requests to fetch co-related information.
  • You can use GraphQL as a backend server or connect with existing backend infrastructure to query data.
  • With GraphQL, you clearly define data types that in turn decrease confusion between the client and the server.
  • In a GraphQL application, the client can only make a single query and receive a response with the data it requires delivered consistently thereby reducing the number of network calls.
  • Using GraphQL sets a single source of truth for data fetching in your application.
  • Consider the sample request where you fetch a list of employees with the following parameters id, name, email, and age.

Why Use SQL in Your Application?

Structured Query language (SQL) is a popular query language that has been around since the '70s. It is still frequently used as a query language.

SQL is loved by developers as well as data analysts because it integrates well with other programming languages. SQL can be used in practically any application built with major programming languages such as PHP, Java, or JavaScript.

SQL is a high-level level that is super-fast. It is also fairly easy to learn as it uses common English terms.

  • A typical SQL syntax to create a new database looks like this:

CREATE DATABASE testdb;

The above command, when executed, will create a database called testdb.

  • Then, to use the just created database, the syntax will be:

USE testdb

  • Next, you will create a table called Employee:

CREATE TABLE Employee (EMPId Int Identity NOT NULL,

EmpNo varchar (10), SSN varchar (10), DOB DATE,

CreatedDt Datetime, CreatedBy varchar(10)); 

For an even more in-depth dive into SQL commands, please read SQL Server CRUD Operations.

Overview of GraphQL vs. SQL The Differences and Similarities And Why You Should Use Them

Differences and Similarities Between GraphQL and SQL

GraphQL as a query language allows you to know exactly the shape of the data you are expecting from the server. This is advantageous because it will enable you to structure your data-driven applications flexibly.

For a more visual comparison between SQL and GraphQL, we provided the below table to illustrate that:

Features GraphQL SQL
Payload data structure GraphQL responses are JSON-based payloads to send/receive data
Code Need to use third-party tools like GraphQL Code Generator to generate client node.
 Flexibility GraphQL is flexible to work with. It is easily customizable to suit what you want. Not flexible.
Data fetching control Efficient fetching of data. Only critical data will be fetched from the server. GraphQL was designed in a manner to allow the client to request only the data it needs. The server would only provide the data that the client requested, even if it might be able to send more data to the client for a single request. SQL on the other hand does not have the ability to allow the client to request a single, exact data it needs.
HTTP 1.1 vs
HTTP 2
Follows the request-response model. It can work with either HTTP version but is typically built with HTTP 1.1. SQL Server's ability to publish data over HTTP is made possible through SQLISAPI.
Speed GraphQL is fast in terms of processing requests and returning responses back. Though SQL is a high-level domain language, it is very fast. As Travis Addair said, data organization (partitions, indexes), network (for short queries), and scale (number of machines, resources for each machine) bounds the performance of SQL. Still, SQL is fast because the database can decide how to get the data.
Developer-friendly
Learning curve Learning curve. Easy to learn.
Knowledge of the structure and the shape of data 🛑
Operations for data manipulation GraphQL performs two operations (read operation) and a mutation (write operation). SQL performs the CRUD operations that are CREATE, READ (SELECT), UPDATE, and DELETE.
Security GraphQL's flexibility can introduce security vulnerabilities that you need to care about. SQL server is designed with security in mind, it has data encryption features, limit access, and authorization, among others.
Data-agnosticism GraphQL is agnostic of the data source. SQL is cognizant of the data source.
Query structure With GraphQL, you can make simple queries that retrieve or update a part of your data that matches a simple pattern. SQL is a powerful general-purpose query language that allows you to define very complex queries in a declarative way.
HTTP Status code responses GraphQL queries always return an HTTP status code of 200, regardless of whether or not the query was resolved successfully. This makes it difficult for error handling and monitoring. SQL queries return the relevant HTTP status code. If your request was successful, you get the corresponding relevant HTTP status code response. If not successful, you get the corresponding HTTP status code response, for example, HTTP 400.
Monitor your database activities from the browser With the Apollo Client Developer Tools Chrome extension, you could debug your Apollo-Client-based GraphQL app right from your browser. This is exciting because queries are sent from your already configured Apollo Client instance, so you don't have to manually pass in headers and other data or manually configure a GraphiQL page in your app. Learn more here. You can also test your SQL commands, monitor your SQL database from your browser using SQLPad.

FAQ

Is SQL Related to GraphQL?

SQL is not the same as GraphQL, and they are not directly related. While GraphQL is used to send and receive data between client and server with the minimum number of HTTP requests.

Is GraphQL better, or can it be an alternative to SQL?

No. Both are used for different purposes. Graph databases are great for specific projects that will require non-relational databases whereas the vast majority of data is relational.

Is GraphQL a database language like SQL?

No, GraphQL is a query language used for remote client-server communications.

Does GraphQL generate SQL?

No. The abstraction between the server and database itself like the Apollo server will eventually query using SQL.

How does GraphQL relate to Memphis.dev?

Memphis is a next-generation message broker that among its use cases - enables asynchronous communication between services.

Memphis built schemaverse that provides a robust schema store and schema management layer on top of memphis broker without a standalone compute or dedicated resources, and it supports different data formats like protobuf, JSON, and GraphQL.

Conclusion

In this article, you read what GraphQL and SQL query languages are, the differences and their similarities, the advantage of one over the other, and finally, you read about some reasons why you should use one over the other in your next project.

You should consider using GraphQL if you intend your API to be a NoSQL database. In contrast, consider using SQL if you use a query language to manage your relational database.

It is worth noting that according to StackShare, the social media giants use GraphQL as their query language and this translates to GraphQL having a broader approval. 

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