Rest is an acronym for representational country transfer and an architectural fashion for allotted hypermedia structures. Roy fielding first presented it in 2000 in his well-known dissertation.

Like different architectural patterns, the Rest has its guiding standards and constraints. Those concepts need to be happy if a provider interface wishes to be referred to as restful.

Graphql is a question language (that’s what the “Ql” stands for) for APIs and a runtime for pleasurable the ones queries together with your current records. It's far used to load information from a server to a customer -- it’s a manner to get statistics from an API into your utility. And as you’ll see, it does this in a much more efficient way than traditional strategies and offerings.

With REST API, we typically look at an endpoint for each request. This would be for every query, whether that is a Select, Insert, Update, or Delete. Each endpoint represents a different call to the Database. This is not the case for GraphQL. Instead, GraphQL implements only a single endpoint. All calls are made through a single endpoint.

This is not to say that GraphQL is unable to Select, Insert, Update, or Delete. All of these types of calls may still be made. However, it is all done through a single endpoint. There are then two separate “Types”, which are query and mutation. These allow you to do exactly as they say. Either you can query, or you can mutate, which could be an Insert, an Update, or a Delete.

With a REST API, we know that data is organized in JSON format. With GraphQL, we use a graph structure instead. These nodes are more schema-defined than an object. This graph format is more custom to GraphQL, as it creates its custom structure. This allows for greater flexibility, as there isn’t a de-facto format like there is with REST.

With REST, the size of resources is determined by the server. In GraphQL, by contrast, a server allows clients to request data at more specific times, which ultimately determines what resources are available and when they are available.

Because GraphQL uses only a single endpoint, relationships are assigned based on the schema your graph is set up in. This means that a relationship between tables is established instead of using different endpoints, because it may only use the single endpoint.

As previously mentioned, GraphQL is made to be flexible. It can therefore return a more customized subset of data to better reflect what information is required. What this means is to first take a database and fetch it with a REST API. If we’re needing several tables worth of information, we would need different requests. Further, if we needed a specific column from a table, we would need a call to get that information as well. While we develop, we see that we have to put that data into an object, so there may be unnecessary data that is saved into that object. With GraphQL, fetching data is more custom and has more freedom. It could limit the number of calls required, or even keep the calls at only one. If certain columns are desired, those columns could be gathered without needing to save others in an object. In theory, this could then speed up your API calls.

There are a few API issues that REST may pose. One is Over-fetching. The example is like what was given above, where only certain data is needed. GraphQL avoids over-fetching data by allowing the information to be specifically requested, therefore only getting what is needed.

The next is Under-fetching. Again, like mentioned above, this would be where you need multiple requests to gather the information you need because making a single request would not return everything needed. The flexibility of GraphQL ensures you can get the data you need with fewer calls, potentially only a single call, because of how customized it is.

An issue that could potentially be resolved is the issue of speed. Theoretically, if you are requiring fewer calls, and if you are pulling less data than entire tables, your queries should run faster.

Another slowdown could come from development. If a new table is needed, with a REST API you would write your function to gather the data, build the object, but you would also have to then create an endpoint to handle that “GET”. With GraphQL, you don’t need to create that extra endpoint, because we only work with one. Even if only a little, it does speed up the development process.

Although maybe not a large factor, being flexible allows for much easier scaling. Being able to make alterations to schemas or queries without harming the existing schemas/queries allows for a much easier implementation when making data larger. This means that changes leave a minimal impact on the current architecture, which is more encouraging when making large changes. Keeping in mind that resourcing is also better dealt with by the server, it is also very helpful that GraphQL does typically speed up requests. Being so flexible allows for further growth. It is also faster to write, as there would not be as much code to change. With the graph structure, it is readable even to non-technical users, making it easier for others to review your code and understand it.

With GraphQL growing in popularity, documentation and support are also growing. This makes finding answers or even helping to resolve issues easier. Although REST allows for the same, it is still promising that the same support can be found for GraphQL.

All being said, there are a few drawbacks to GraphQL. One major drawback is the learning curve. While with REST you can typically jump in even as a beginner, GraphQL takes more research to understand. I read several articles, and still, I’m thinking I need to understand just a little better before I give it a go.

GraphQL is still growing, and so hasn’t perfected all of its flaws. But so far, it offers more flexibility than REST, and also fixes some of the drawbacks, such as under-fetching or over-fetching. GraphQL also uses a strong “Type” system in its format and uses a graph instead of JSON.

With REST, each request uses a different endpoint. However, with GraphQL, you use only a single endpoint. Further architecture differences occur, such as how the server will determine resources.

In the end, I think whether to use, GraphQL or REST is more up to you and your ambition. GraphQL seems very interested, granted there is quite a learning curve. I think GraphQL has wonderful potential to be used in some of my projects to optimize the requests. That being said, this may not be the case for everyone. As I’ve said in other posts, you know your project than anyone else does. But I would encourage you to do a little research on what GraphQL can be used for to see if this challenge is for you. For now, I’m very interested in learning more about GraphQL, so be on the lookout for another more in-depth post about it. Until then, cheers!

Today we will discuss between Rest and GraphQl.

Rest vs. GraphQl

GraphQL is a query language for APIs that enables declarative data fetching in order to give the client the power to specify exactly the data that is needed from the API. It makes easier to evolve APIs over time.

Now that we know what GraphQL is, I want to clarify what it is not, as I feel that there is still some confusion about it.

Firstly, it does not have anything to do with databases. It is not an alternative to SQL or a brand new ORM.

Secondly, it is not a REST replacement, but an alternative. You don't have to pick between one and the other, they can happily co-exist in the same project.

Last but not least, GraphQL is not complicated or scary. It is quite easy to understand its declarative nature and exactly how it is possible to take the best from it.

GraphQL was developed internally by Facebook in 2012 before being open-sourced in 2015, with its stable version released just in June 2018. On 7 November 2018, the GraphQL project was moved from Facebook to the newly-established GraphQL Foundation, hosted by the non-profit Linux Foundation.

Lee Byron, GraphQL's creator, aims to make GraphQL omnipresent across web platforms.

GraphQL is being used by teams off all sizes, in many different environments and languages. The main companies that are using GraphQL are Facebook, Github, Pinterest and Shopify.

REST was defined by Roy Fielding, a computer scientist that presented the REST principles in his PhD dissertation in 2000.

REST (Representational State Transfer) is a software architectural style that defines a set of constraints which make any web service – a true RESTful API.

Client-server architecture means that the user-interface concerns should be separated from the data storage concerns to improve the user interfaces portability across multiple platforms.

A stateless server does not persist any information about the user who uses the API. This means that the server does not remember if the user is sending is first request or not.

REST API responses must define themselves as cachable or non-cachable to prevent clients from providing any inappropriate data that can be used on future requests.

A Layered system means that if a proxy or load balancer is placed between client and server, the connections between them should not be affected, and the client did not know if is connected to the end server or not.

A Uniform interface suggests that it should be a uniform way of interacting with a given server despite the device or application type (website, mobile app). The main guideline is that each resource has to be identified on requests.

Why was GraphQL created if there's already REST

There are two main reasons why companies such as Facebook, Netflix and Coursera started developing alternatives to REST:

In the early 2010s, there was a boom in mobile usage, which led to some issues with low-powered devices and sloppy networks. REST isn't optimal to deal with those problems;

As mobile usage increased, so did the number of various front-end frameworks and platforms that run customer applications. Given REST's firmness, it was harder to develop a single API that could fit the prerequisites of each customer.

      If we go even further, we realize that the main reason why an alternative solution was identified was because most of the 
      data used in modern web and mobile applications has a graph shape. For instance, news pieces have comments, and 
      those comments may have features such as likes or spam flags, which are created or reported by users. This example 
      describes how a graph looks like.

      Consequently, Facebook started developing GraphQL. At the same time, Netflix and Coursera were also working on 
      alternatives themselves. After Facebook open-sourced GraphQL, Coursera dropped their efforts and adopted the new 
      tech. Netflix, however, continued developing their own REST alternative and later open sourced Falcor.

In this section I will go point by point through a practical example, comparing REST to GraphQL in order to demonstrate the flexibility of Facebook's query language.

Imagine that you have a blog, and you want the front page to show all the latest posts. In order to achieve this, you need to fetch the posts, so you will probably do something like this:

But what if you want to see the author as well? You have three options to achieve this:

Modify the resource to also return the author:

Create a new resource that returns the posts with the author:V

The goal is to provide a brief explanation to anyone who still has not got to know GraphQL, clarify exactly what it does better than REST.

GraphQL vs Rest: which one is better

GraphQL is a query language and server-side runtime for application programming interfaces (APIs) that prioritizes giving clients exactly the data they request and no more. 

GraphQL is designed to make APIs fast, flexible, and developer-friendly. It can even be deployed within an integrated development environment (IDE) known as GraphiQL. As an alternative to REST, GraphQL lets developers construct requests that pull data from multiple data sources in a single API call. 

Additionally, GraphQL gives API maintainers the flexibility to add or deprecate fields without impacting existing queries. Developers can build APIs with whatever methods they prefer, and the GraphQL specification will ensure they function in predictable ways to clients.

GraphQL offers many benefits over REST APIs. One of the main benefits is clients can dictate exactly what they need from the server, and predictably receive that data.

For example, imagine you have the following schema:

Now let’s say that you just needed to get a User‘s name. If you had a REST API, you would typically receive the entire User object back in your response. This leads to over-fetching and can result in performance issues. With GraphQL, you only receive the data you explicitly request.

Here’s what our User name query would look like:

And here’s what our response would look like:

Another big benefit is the ability to retrieve many resources in a single request. Continuing with our example schema, imagine we want to also fetch the names of our User‘s friends as well. For a traditional REST API, we would probably need to make an additional request to a /friends?id=X endpoint, passing in our User‘s ID.

We can simply append our friend's property to our query and receive all our names in a single request:

Another benefit is that it is strongly typed which allows API consumers to know exactly what data is available, and in what form it exists. According to the docs: “Every GraphQL service defines a set of types which completely describe the set of possible data you can query on that service. Then, when queries come in, they are validated and executed against that schema.”

While GraphQL has many advantages over traditional REST APIs, there are several key disadvantages as well.

One disadvantage is that queries always return an HTTP status code of 200, regardless of whether or not that query was successful. If your query is unsuccessful, your response JSON will have top-level errors key with associated error messages and stack trace. This can make it much more difficult to do error handling and can lead to additional complexity for things like monitoring.

Another disadvantage is the lack of built-in caching support. Because REST APIs have multiple endpoints, they can leverage native HTTP caching to avoid re-fetching resources. With GraphQL, you will need to set up your caching support which means relying on another library or setting up something like globally unique IDs for your backend.

This leads us to the final disadvantage: complexity. If you have a simple REST API and deal with data that is relatively consistent over time, you would be better off sticking with your REST API. For companies that deal with rapidly-changing data, and have the engineering resources to devote to rearchitecting their API platforms, GraphQL can solve many of the pain points experienced with REST APIs.

GraphQL provides an interesting solution to common hurdles faced when using REST APIs. While using GraphQL has several downsides, if you find yourself working with rapidly-changing data at scale, it could be a great solution for your business. To learn more about it, check out the docs. And if you’re looking for a more fully-fledged GraphQL solution, Apollo provides an easy way to get started on both the client and server sides.

SQL stands for Structured Query Language which is a language used by databases. This language allows to handle the information using tables and shows a language to query these tables and other objects related (views, functions, procedures, etc.). Most of the databases like SQL Server, Oracle, PostgreSQL, MySQL, MariaDB handle this language (with some extensions and variations) to handle the data.

SQL Queries can be used to retrieve large amounts of records from a database quickly and efficiently.

SQL joins two or more tables and shows it as one table to the user.

It is easy to use because it is like the structured English language so it does not need any coding. 

SQL can be used in the programs in servers, laptops, PCs, and even some mobile phones.

With the SQL language, each user can have a different view from the other. 

SQL is used for linking end computers and databases. Thus, providing client-server architecture.

SQL has a complex interface that makes it difficult for some users to access it.

The programmers who use SQL don’t have full control over the database because of the hidden business rules.

Some of the databases go to the proprietary extensions to standard SQL for ensuring the vendor lock-in.

The operating cost of some SQL versions makes it difficult for some programmers to access it.

If you have no logic between your GraphQL resolvers and your backend’s database, one can just translate the GraphQL query to a SQL statement. That’s why it’s so “easy” for GraphQL solutions like Hasura to create GraphQL CRUD operations for you.

However, in most cases, your GraphQL resolvers have business logic. For instance, maybe you don’t want to fetch all books by an author, but some statistics for your frontend visualization to learn more about the books written by an author. Then the GraphQL resolver would fetch all books by an author from the database, but prepare the data for the visualization before passing it to the frontend.

Let's find the difference between GraphQL and SQL.

GraphQL vs SQL

I've been working with mongoose for a quite a while now and recently started exploring graphql. In mongoose, we can use specific fields like so:

User.findById(id).select('+name +email');


We can also do the same in a graphql query. So what's the difference? In the resolve function in graphql, we will anyways get a list of all users. Doesn't graphql add extra delay in response?

Graphql vs Mongoose Query Methods

I'm in the process of learning about the MERN stack by following this book https://www.amazon.com/Pro-MERN-Stack-Development-Express-dp-1484243900/dp/1484243900/ref=mt_paperback?_encoding=UTF8&me=&qid= but even if it is a very recent one (published in 2019) the code examples are a travesty.

Basically when I try to start the server contained in this repo https://github.com/vasansr/pro-mern-stack-2/tree/05.02-graphql-schema-file with the command npm start the app crashes and it returns an

Error: Cannot find module 'graphql/validation/rules/PossibleTypeExtensions'

The code in the repo was published directly by the author so I don't exactly know how to solve this, could someone help me?

Cannot find module 'graphql/validation/rules/PossibleTypeExtensions'

GraphQL consists of a type system, query language and execution semantics, static validation, and type introspection, each outlined below. To guide you through each of these components, we've written an example designed to illustrate the various pieces of GraphQL.

Falcor lets you represent all your remote data sources as a single domain model via a virtual JSON graph. You code the same way no matter where the data is, whether in memory on the client or over the network on the server.

What is the difference between Falcor and GraphQL (in the context of Relay)

What is the difference between Falcor and GraphQL?

Graphql is great and I've started using it in my app. I have a page that displays summary information and I need graphql to return aggregate counts? Can this be done? 

Can graphql return aggregate counts?

I am consuming a particular GraphQL endpoint and although I am supplying a clean JSON structure as a query, when I get the results I get "edges" and "node" tags. It seems as if it is polluting my data with no obvious benefit. Why is it there and is it possible to get rid of those for faster and simpler parsing of data? 

In GraphQL what's the meaning of "edges" and "node"?

With REST we can use Swagger, RAML or other technologies to document our API and generate an HTML documentation that our consumers can read without any need of interaction with the servers.

Does something similar exist for GraphQL? Is there any way to generate a documentation of resources and properties?

Document a GraphQL API

GraphQL has mutations, Postgres has INSERT; GraphQL has queries, Postgres has SELECT's; etc., etc.. I haven't found an example showing how you could use both in a project, for example passing all the queries from front end (React, Relay) in GraphQL, but to a actually store the data in Postgres.

Does anyone know what Facebook is using as DB and how it's connected with GraphQL?

Is the only option of storing data in Postgres right now to build custom "adapters" that take the GraphQL query and convert it into SQL?

How to connect GraphQL and PostgreSQL

I'm making Next.JS app with Mongoose (MongoDB) and GraphQL.

During the work, the question arose about how to properly combine these two schemes? In my case I got two identical schemes via different technologies. May be each of them should do different things (for example validation) or something like that?

How combine GraphQL and Mongoose schemas correctly?

Is there a way to source wordpress woocomerce products by locale. I am using gatsby with graphql. So far i can source all the pages and posts etc. by locale but can't find an option for woocomerce products. 

Source woocomerce products by locale

I have established a working flow in using Auth0 jwt to authenticate to my API. It currently follows a REST architecture. The Auth0 token is passed in a http-only cookie, and it provides an Auth user ID, which I have used to pull user-specific records from a database, as well as confirm the identity of the individual calling the API through the client.

My question is, how do I replicate this pattern in a graphQL architecture? I am currently using Postgraphile and Relay, however I am struggling to see how I can securely pass the Auth user ID in an HTTP only way to minimize vulnerabilities. Is there a way this can be done in a graphQL request?

Using Auth0 user ID in identity management for GraphQL

I am way too confused how everything works together in AWS.

First of all I created an Android app with AWS Amplify.

Now I have a Php webserver (Laravel) which I also would like to include with AWS.

I want to make some requests from my webserver to access and manipulate the data from AWS Amplify, how do I achieve that, am I using the right AWS tools, how can I gather all the important information?

How can I access my AWS Amplify data with graphql / rest api?

What is the query syntax for getting the list of all previously created tables? And how can I then view selected table fields? 

GraphQL API (Astra DB) - the list of existing tables and fields

Mongodb offers the possibility to avoid over-fetching of data via projection so select only what you wont to have from fields of the document... GraphQL is offering the user the possibility to select only what he wont to have from API fields.

Is there any way based on java (spring) to forward the selected user input (from DataFetchingEnvironment) to mongodb (Query) because the API and document (collection) are almost the same...

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Trending Blogposts on graphql

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openWhat is the difference between Falcor and GraphQL?