GraphQL is well known as a Query Language for APIs that allows declarative data fetching to give the client the power to specify the data required from the API. GraphQL makes it easier to evolve APIs over time. GraphQL was developed by Facebook in 2012 before being Open-sourced in 2015.
REST API is defined as a Software Architectural Style built to guide the development and design of the architecture for the World Wide Web. REST APIs define a set of constraints on how the architecture of a distributed system should behave.
This blog highlights the key differences between GraphQL and REST API to help you make an educated decision regarding which one suits your business requirements best.
Table of Contents
- What is GraphQL?
- What is REST?
- Why was GraphQL Developed when REST was there?
- Main Differences between GraphQL vs REST
- What is REST Good for?
- What is GraphQL Good for?
- Advantages of GraphQL
- Disadvantages of GraphQL
- Advantages of REST
- Disadvantages of REST
- GraphQL vs REST API: Summary Table
- GraphQL vs REST API: Which is Better?
What is GraphQL?
GraphQL is a Query Language that can be used to work with APIs. It enables the client to make HTTP requests and get responses.
As the name suggests, any set of information in GraphQL is seen in the context of a graph. Nodes defined under the GraphQL Schema System are used to depict objects. Edges between these nodes are used to represent the connection between the nodes of a graph.
This ensures clear relationships between queries and improves the connectivity between objects. GraphQL can also allow the users to request data from various resources using a single request.
As opposed to making multiple requests to fetch data, you can use GraphQL to make ad-hoc queries to a single endpoint and access all the necessary data.
GraphQL also allows the user to specify the exact type of data to be received from the server. This predictable data structure makes it highly efficient and readable. GraphQL is very easy to understand. Its declarative nature allows you to get the best out of it.
What is REST?
REST APIs provide a flexible, lightweight way of integrating applications. REST APIs allow you to search for some items, and then the results will be returned from the service you requested from. A REST API has the following components:
- The Headers: Headers refer to the Authentication Mode and the Content Types.
- The Method: There are various methods that you can use to call a REST API, the most common ones being POST and GET. The GET method is used to gather information while the POST method can be used to send information to the resources on the web.
- The Endpoint: The Endpoint is defined as the URL of the resource to which you are going to place the requests. For instance, https://api.powerbi.com/v1.0/myorg/.
- The Data or Body: This refers to the textual data in the form of JSON, which needs to be sent to the resource.
Here are a few REST design principles that are integral for the smooth functioning of a REST API:
- Client-Server Decoupling: In REST API design, Server and Client applications must be completely independent of each other. The only information available to the Client-side should be the URI of the requested resource. Similarly, a server application shouldn’t change the client application other than passing the requested data through HTTP.
- Statelessness: REST APIs are Stateless. This means that each request should contain all the information required to process it. This can also mean that REST APIs don’t require any server-side sessions. Server applications aren’t permitted to store any data related to the client request.
- Cacheability: Whenever possible, resources should be Cacheable on the Server or Client-side. Server responses should also contain information on whether caching is allowed for the delivered resource. You should aim for improving performance on the client side while increasing scalability on the server side.
- Uniform Interface: All API requests for the same resource should look the same, irrespective of where the request comes from. The REST API should ensure that the same piece of data, like the email address or name of a user, belongs to only one Uniform Resource Identifier (URI). Resources shouldn’t be too huge but should contain every piece of information that the client may need.
- Layered System Architecture: In REST APIs the responses and calls go through different layers. You shouldn’t assume that the Client and Server applications connect directly to each other. There may be various intermediaries involved in the communication loop. Therefore, REST APIs need to be designed such that neither the server nor the client can tell whether it communicates with an intermediary or an end application.
Simplify your REST API ETL with Hevo’s No-code Data Pipeline
A fully managed No-code Data Pipeline platform like Hevo Data helps you integrate and load data from 100+ Data Sources (including 40 Free Data Sources like REST APIs) to a destination of your choice in real-time in an effortless manner.Get Started with Hevo for Free
Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance. Its strong integration with umpteenth sources allows users to bring in data of different kinds in a smooth fashion without having to code a single line.
Check out some of the cool features of Hevo:
- Completely Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.
- Transformations: Hevo provides preload transformations through Python code. It also allows you to run transformation code for each event in the Data Pipelines you set up. You need to edit the event object’s properties received in the transform method as a parameter to carry out the transformation. Hevo also offers drag and drop transformations like Date and Control Functions, JSON, and Event Manipulation to name a few. These can be configured and tested before putting them to use.
- Connectors: Hevo supports 100+ integrations to SaaS platforms, files, databases, analytics, REST APIs, and BI tools. It supports various destinations including Amazon Redshift, Snowflake Data Warehouses; Amazon S3 Data Lakes; and MySQL, SQL Server, TokuDB, DynamoDB, PostgreSQL databases to name a few.
- Real-Time Data Transfer: Hevo provides real-time data migration, so you can have analysis-ready data always.
- 100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
- Scalable Infrastructure: Hevo has in-built integrations for 100+ sources that can help you scale your data infrastructure as required.
- 24/7 Live Support: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support calls.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.
Why was GraphQL Developed when REST was there?
The main reasons why GraphQL was developed as a viable alternative to REST APIs are as follows:
- The early 2010s marked a boom in mobile usage, which led to some issues with sloppy networks and low-powered devices. REST APIs weren’t the best at dealing with these problems.
- With the increase in mobile usage, the number of front-end platforms and frameworks that run client applications also increased. Owing to REST’s inflexibility, it was very hard to develop a single API that could easily fit the requirements of every client.
- The primary reason why GraphQL was developed as an alternative was that most of the data used in mobile applications and the modern web has a graph shape. For example, news pieces have comments, and these comments may have features such as spam flags or likes, which are created or reported by users. This describes how a graph looks like.
Main Differences between GraphQL and REST
GraphQL and REST are two design approaches that focus on the same function: data transmission through internet protocols such as HTTP. However, the implementation is where they branch out. Here are a few factors you can analyze to shed light on the topic of GraphQL vs REST:
- GraphQL vs REST: Usability
- GraphQL vs REST: Performance
- GraphQL vs REST: Security
- GraphQL vs REST: Popularity
- GraphQL vs REST: Data Fetching
GraphQL vs REST: Usability
When it comes to GraphQL vs REST usability, the two differ significantly in terms of both Versioning and Predictability. An important benefit of GraphQL is its high predictability.
It allows you to send a request to your API and get the exact results you require without unwanted inclusions. GraphQL queries return predictable results which significantly improves their usability.
REST’s behavior, on the other hand, varies based on the HTTP and URI methods used. This can make it unclear for an API consumer to know what to expect when calling an endpoint.
In terms of Versioning, REST doesn’t have standardized and clear guidelines for it. This means that every provider is free to implement their approach. On the other end of the spectrum, you have GraphQL. It follows a very simple approach to versioning: don’t version APIs.
Therefore, if you were to compare GraphQL vs REST API in terms of versioning and predictability, GraphQL’s simplicity gives it an edge over REST.
GraphQL vs REST: Performance
In terms of GraphQL vs REST performance, the inclination for Over-fetching and Under-fetching in RESTful services gives GraphQL a clear edge. Since REST APIs have inherently rigid data structures designed to return the stipulated data whenever they get hit, you may end up accumulating unwanted data or be forced to make multiple calls before getting the relevant data. These inadequacies can escalate the time it takes for the server to return the requested information.
On the contrary, GraphQL uses a flexible style that allows you to retrieve what you need in a single API request. After defining the structure of the information you need, the same structure will be returned to you from the server, which avoids over-fetching and under-fetching.
Generally, the GraphQL vs REST debate on performance flags GraphQL as the winner, but there are a few use cases where REST APIs are a better alternative. For example, in cases where caching is desired to expedite API calls.
GraphQL vs REST: Security
When talking about GraphQL vs REST in terms of security, the credit seems to be leaning towards REST. REST provides several ways to enforce the security on your APIs.
For instance, you can ensure REST API security by implementing multiple API authentication methods like HTTP authentication. Here, sensitive data is sent in HTTP headers, through JSON Web Tokens, where sensitive data is sent as JSON data structures, or through OAuth 2.0 mechanisms.
GraphQL also provides some measures to ensure your APIs’ security, but they are not as mature as those of REST. For instance, although GraphQL assists in integrating data validation, users are left to figure out how to apply authorization and authentication measures on top.
GraphQL vs REST: Popularity
In terms of popularity, the GraphQL vs REST debate leans towards REST APIs. For instance, according to a State of API 2020 Report, around 82% of the surveyed API consumers and practitioners use REST-based OpenAPI authentication, while only 18% use GraphQL.
GraphQL vs REST: Data Fetching
In terms of data fetching in GraphQL vs REST, REST API gathers data by accessing multiple endpoints. Using the hierarchy, takes different routes or endpoints.
Like /user/id will be one endpoint to fetch the user data, /user/id/posts will be another endpoint to get all posts of the user, and /user/id/followers will fetch a list of followers of the user.
On the other hand in GraphQL, you can simply send a query to the GraphQL server that includes the data requirements and the server will respond with a JSON object.
What is REST Good for?
Here are a few use cases where leveraging REST APIs is a good option:
- Error Reporting and Monitoring: REST allows you to build a monitoring system based on API responses. GraphQL doesn’t provide the facility for this feature since it always returns a 200 OK status response.
- Non-existent HTTP Caching Mechanism: Nowadays, all browsers offer an implementation of the HTTP cache to easily avoid refetching resources. It is also used to identify if two resources are the same. GraphQL doesn’t allow you to get a globally unique identifier for a given object because you’re using the same URL for all the requests. You will have to set up your cache on GraphQL for this.
- Resource Attacks: GraphQL allows you to query exactly what you want whenever you want it. But, this can lead to some serious security complications. For example, if a malicious party attempts to submit an expensive nested query to overload your database or server and your server doesn’t have the right protections, you might fall victim to DoS (Denial-of-Service) Attacks.
What is GraphQL Good for?
Here are a few use cases when leveraging GraphQL can come in handy:
- GraphQL allows the users to fetch the right amount of data to render a specific view easily.
- GraphQL works best for businesses aiming to build mobile-responsive platforms. Mobile-responsive platforms expect the application to be responsive with low latency which can be provided by GraphQL due to its simple architecture.
- GraphQL uses its type system to define the scheme of an API, with its syntax SDL (Schema Definition Language). It serves as a contract between the server and the client to define how a client can access the data. This allows the front-end and back-end teams to work independently since the front-end can be easily tested with mock data. The schema also provides Type Safety since it can catch type errors early.
Advantages of GraphQL
Some of the advantages of GraphQL are listed below:
- It helps to query batching and caching.
- GraphQL automatically keeps documentation in sync with APIs.
- It is hierarchical and product-centric.
- You can fetch data with a single API call.
- GraphQL is a strongly typed language that means queries are executed within the context of the system.
- It provides declarative query language.
Disadvantages of GraphQL
Some of the disadvantages of GraphQL are listed below:
- Missing design patterns for complex apps.
- Overkill for small applications.
- Performance issues with complex queries.
- It uses a single endpoint instead of following the HTTP caching.
Advantages of REST
Some of the key advantages of REST are listed below:
- The protocol becomes easy to develop across various projects.
- You can create process instances explicitly.
- Developers can build an API that can meet a user-specific need.
- REST API is very easy to build and adapt.
- It enables you to scale software without any difficulty.
Disadvantages of REST
Some of the key disadvantages of REST are listed below:
- There is no way to get limited fields.
- Poor data searching facilities.
- Query validation is not available.
- Manipulating nested resources is not possible.
- It doesn’t maintain the states of a previous interaction between client and server.
GraphQL vs REST API: Summary Table
Here is a summary table of a few key differences for the topic GraphQL vs REST API to give you a better idea:
|1.||GraphQL leverages a Client-driven architecture.||REST utilizes a Server-driven architecture.|
|2.||GraphQL only supports JSON as a way of representing data.||REST supports various data formats to make it convenient for its users.|
|3.||GraphQL lacks an automatic caching mechanism.||REST, as opposed to GraphQL, implements caching automatically during its operations.|
|4.||API Versioning isn’t available in GraphQL.||REST supports various API versions.|
|5.||GraphQL is defined as a query language that offers flexibility and efficiency in solving common problems when integrating APIs.||REST is defined as an architectural style that is largely viewed as a conventional standard for developing APIs.|
|6.||GraphQL is deployed over HTTP through a single endpoint that offers the full capabilities of the exposed service.||REST is deployed over a set of URLs where each one of them can expose a single resource.|
|7.||Error Identification in GraphQL is complex and involves handling HTTP Status Codes.||REST, on the other hand, can use HTTP Status Codes to identify errors easily.|
|8.||GraphQL only uses GraphiQl for documentation.||REST offers a wide range of options for automated documentation such as API and OpenAPI blueprint.|
GraphQL vs REST API: Which is Better?
To conclude the discussion on GraphQL vs REST so far, the answer to this question is subjective and depends heavily on your specific project requirements.
For instance, if you wish to infuse something new into your API development using a modern design style that doesn’t have to make multiple round trips to fetch data, GraphQL might be your best bet.
However, if you are looking to use a tried-and-proven technique that offers robust native authentication or caching, then you should go with REST.
Being aware of the tradeoffs and constraints that lie underneath each API design style is the key to picking the option that best suits your requirements. You could even try deploying a mix-and-match approach that uses both REST and GraphQL.
Irrespective of your choice, you should focus on designing an API product that meets the needs of all the participants in the API value chain: the API Consumer (Developer), the API Provider, and the End-user (Customer).
This blog talks about the crucial factors for the GraphQL vs REST discussion to help you understand them better. It gives a brief introduction to REST and GraphQL before diving into GraphQL vs REST.
Extracting complex data from a diverse set of free data sources such as REST APIs can be a challenging task and this is where Hevo saves the day!Visit our Website to Explore Hevo
Hevo Data offers a faster way to move data from 100+ data sources such as SaaS applications or its native REST API connector that can help connect with a variety of non-native/custom sources or Databases into your Data Warehouse to be visualized in a BI tool. Hevo is fully automated and hence does not require you to code.
Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.