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

 I am searching for a solution to expose an Azure SQL DB table over the Azure API Management and then allow a Kubernetes hosted app to talk with the Azure SQL DB over this API. What would be the less time consuming approach for building this API to expose the table? I have found doc for couple of solution, but coming from the BigData world, I couldn't figure it out which is worth to invest the time and to build it. Any suggestion where should I take a closer look? 

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How to fetch OAuth2.0 Access Token and use this token to call RESTFul Web services using Java client code

I have read articles about the differences between SOAP and REST as a web service communication protocol, but I think that the biggest advantages for REST over SOAP are:

REST is more dynamic, no need to create and update UDDI(Universal Description, Discovery, and Integration).

REST is not restricted to only XML format. RESTful web services can send plain text/JSON/XML.

But SOAP is more standardized (E.g.: security).

SOAP vs REST (differences)

I have a WCF service and I want to expose it as both a RESTfull service and as a SOAP service. Anyone has done something like this before? 

REST / SOAP endpoints for a WCF service

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Django or Firebase for a project with few users

I am trying to recreate this create a new card API, but based on docs, I'm not sure how should I pass the data required, should it be inside the query parameters (req.params to collect the data), for example /1/cards?name=cardName&desc=cardDescription, or should it be inside the req.body? 

Reading the API documentation

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?

I am inspecting a pattern that's in the salesforce developer web page.

In that sample, while we click on a link we will likely be redirected to the salesforce login page. If the log is a success, then an access token is issued.

I don't need my utility to redirect to the salesforce login web page. 

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