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.
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.
GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.
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.
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 a high-level level that is super-fast. It is also fairly easy to learn as it uses common English terms.
CREATE DATABASE testdb;
The above command, when executed, will create a database called testdb.
CREATE TABLE Employee (EMPId Int Identity NOT NULL, EmpNo varchar (10), SSN varchar (10), DOB DATE,
For an even more in-depth dive into SQL commands, please read SQL Server CRUD Operations.
GraphQL is an abstraction to SQL, not an alternative nor a replacement.
GraphQL, as a query language, lets you know exactly the shape of the data you expect from the server and reshape it FAST.
For a more visual comparison between SQL and GraphQL, take a look at the following table:
|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
|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.|
|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.|
SQL is not the same as GraphQL, and they are not directly related. GraphQL is an abstraction to SQL, not an alternative nor a replacement.
No. Both are used for different purposes.
No, GraphQL is a query language used for remote client-server communications.
Partially. The abstraction of GQL and processing will eventually query the database using SQL.
Memphis is a next-generation alternative to traditional message brokers.
Like the benefits of using GraphQL, Memphis enables the building of modern queue-based applications that require large volumes of streamed and enriched data, modern protocols, zero ops, rapid development, extreme cost reduction, and a significantly lower amount of dev time for data-oriented developers and data engineers.
Memphis reinvented the use of schemas between microservices using its Schemaverse.
Memphis Schemaverse provides a robust schema store and schema management layer on top of memphis broker without a standalone compute or dedicated resources.
Among the supported protocols, you can find GraphQL, which let’s you declare schemas using GraphQL, and its the only schema management tool that supports GQL.
For more information, please head here
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.