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GraphQL vs. REST API: What’s the difference?


As the conduits through which software components interact and data flows across the internet, APIs are the lifeblood of contemporary web services. API technologies like SOAP (a web services messaging protocol), REST (an architectural style) and GraphQL (a programming language and tool) simplify software development by enabling third-party data and services integration. APIs also enable companies to offer secure service functions and data exchange to employees, business partners, and users.

Despite the many types of APIs, debates about two major paradigms have dominated the conversation in recent years: REST (representational state transfer) and GraphQL. Both offer a range of benefits and thus are deployed for networking projects across the globe. However, they differ significantly in how they manage data traffic. Here, we dissect those differences and discuss how businesses can use REST and GraphQL APIs to optimize their networks.

What are REST and GraphQL APIs?

An understanding of REST and GraphQL APIs individually is necessary for a comparison of the two.


Developed in the early 2000s, REST is a structured architectural style for networked hypermedia applications, which is designed to use a stateless, client/server, cacheable communication protocol. REST APIs, also called RESTful APIs, are the drivers of REST architectures.

REST APIs use unique resource identifiers (URIs) to address resources. REST APIs work by having different endpoints perform CRUD (“create,” “read,” “update” and “delete”) operations for network resources. They rely on a predefined data format—called a media type or MIME type—to determine the shape and size of resources they provide to clients. The most common formats are JSON and XML (and sometimes HTML or plain text). 

When the client requests a resource, the server processes the query and returns all the data that is associated with that resource. The response includes HTTP response codes like “200 OK” (for successful REST requests) and “404 Not Found” (for resources that don’t exist).


GraphQL is a query language and API runtime that Facebook developed internally in 2012 before it became open source in 2015.

GraphQL is defined by API schema written in the GraphQL schema definition language. Each schema specifies the types of data the user can query or modify, and the relationships between the types. A resolver backs each field in a schema. The resolver provides instructions for turning GraphQL queries, mutations, and subscriptions into data, and retrieves data from databases, cloud services, and other sources. Resolvers also provide data format specifications and enable the system to stitch together data from various sources.

Unlike REST, which typically uses multiple endpoints to fetch data and perform network operations, GraphQL exposes data models by using a single endpoint through which clients send GraphQL requests, regardless of what they’re asking for. The API then accesses resource properties—and follows the references between resources—to get the client all the data they need from a single query to the GraphQL server. 

Both GraphQL and REST APIs are resource-based data interchanges that use HTTP methods (like PUT and GET requests) that dictate which operations a client can perform. However, key differences exist between them that explain not only the proliferation of GraphQL but also why RESTful systems have such staying power.

Differences between GraphQL and REST APIs

GraphQL offers an efficient, more flexible addition to REST; GraphQL APIs are often viewed as an upgrade from RESTful environments, especially given their ability to facilitate collaboration between front-end and back-end teams. GraphQL provides a logical next step in an organization’s API journey, helping fix issues that are often encountered with REST.

However, REST was long the standard for API architectures, and many developers and architects still rely on RESTful configurations to manage their IT networks. As such, understanding the distinctions between the two is integral to any organization’s IT management strategy. 

REST and GraphQL APIs differ in how they manage:

Data retrieval

Because REST relies on multiple endpoints and stateless interactions—where every API request is processed as a new query, independent of any others—clients receive every piece of data that is associated with a resource. If a client needs only a subset of the data, it still receives all the data (over-fetching). And if the client needs data that spans multiple resources, a RESTful system often makes the client query each resource separately to compensate for inadequate data retrieval from the initial request (under-fetching). GraphQL APIs use a single GraphQL endpoint to give clients a precise, comprehensive data response in a one round trip from a single request, eliminating over- and under-fetching issues.


In a REST architecture, teams must version APIs to modify data structures, and prevent system errors and service disruptions for the end user. In other words, developers must create a new endpoint every time they make changes, creating multiple API versions and potentially complicating maintenance. GraphQL reduces the need for versioning because clients can specify their data requirements in the query. The addition of new fields to the server does not affect clients without a need for those fields. Conversely, if fields are deprecated, clients can continue to request them until queries are updated.

Error handling

REST APIs should use HTTP status codes to indicate the status or success of a request, and each status code has a specific meaning. A successful HTTP request returns a 200 status code, while a client error might return a 400 status code and a server error might return a 500 status code.

At first glance, this approach to status reporting seems more straightforward, but HTTP status codes are often more useful to web users than to the APIs themselves, especially in the case of errors. REST does not have a specification for errors, so API errors can appear as transport errors or don’t appear with the status code at all. This dynamic can force personnel to read through the status documentation to understand what errors mean or even how errors are communicated within the infrastructure.

With GraphQL APIs, every request—regardless of whether it resulted in an error—returns a 200 OK status code because errors aren’t communicated by using HTTP status codes (except for transport errors). Instead, the system communicates errors in the response body along with the data, so clients must parse through the data payload to determine if the request was successful.

That said, GraphQL does have a specification for errors, so API errors are more easily distinguishable from transport errors. The exact nature of errors appears in the “errors” entry in the response body, which can make GraphQL APIs preferable to build against.

Real-time data

REST doesn’t have built-in support for real-time updates. If an app needs real-time functionality, developers usually must implement techniques like long-polling (where the client repeatedly polls the server for new data) and server-sent events, which can add complexity to the application.

However, GraphQL includes built-in support for real-time updates through subscriptions. Subscriptions maintain a steady connection to the server, allowing the server to push updates to the client whenever specific events happen.

Tools and environment

The REST environment is well established, with a wide range of tools, libraries, and frameworks available to developers. Working with REST APIs nonetheless requires teams to navigate several endpoints and understand the unique conventions and patterns of each API.

GraphQL APIs are relatively new, but the GraphQL environment has grown tremendously since its introduction, with various tools and libraries available for both server and client development. Tools like GraphiQL and GraphQL Playground provide powerful, in-browser, integrated development environments (IDEs) for exploring and testing GraphQL APIs. Furthermore, GraphQL has strong support for code generation, which can simplify client-side development.


REST APIs rely on mechanisms like eTags and last-modified headers to cache API calls. While effective, these caching strategies can be complex to implement and might not be suitable for all use cases.

GraphQL APIs can be more challenging to cache due to the dynamic nature of the queries. However, deploying persisted queries, response caching, and server-side caching can mitigate these challenges and streamline broader caching efforts in GraphQL architectures.

When to use GraphQL and REST APIs

Neither REST nor GraphQL APIs are inherently superior; they’re different tools that are suited to different tasks. 

REST is generally easier to implement and can be a good choice when a straightforward, cacheable communication protocol with stringent access controls is a preferred (for public-facing e-commerce sites like Shopify and GitHub, as one example). Given the under- and over-fetching risks, REST APIs are best for:

  • Businesses that use smaller apps with simpler data profiles
  • Businesses with no complex data querying requirements
  • Businesses where most of the client base uses data and operations in similar ways

GraphQL APIs enable more flexible, efficient data fetching, which can improve system performance and ease-of-use for developers. These features make GraphQL especially useful for building APIs in complex environments with rapidly changing front-end requirements. This includes:

  • Businesses with limited bandwidth, looking to limit calls and responses
  • Businesses that want to combine data points at a one endpoint
  • Businesses whose client requests vary significantly

Though they use different approaches, both GraphQL and REST APIs have the potential to greatly enhance network scalability and server performance. 

Take control of your API environment with IBM API Connect

Regardless of whether you choose to deploy REST or GraphQL APIs—or some combination of the two—your business can benefit from a wide range of potential applications, including implementations in various programming languages (like JavaScript) and integration with microservices and serverless architectures. With IBM API Connect, you can use both API types to optimize your IT infrastructure.

IBM API Connect is a full-lifecycle API management solution that helps you create, manage, secure, socialize and monetize APIs, and promote digital transformation across data centers and cloud environments. This means that both businesses and customers can power digital apps and spur innovation in real time.

With API Connect, enterprises can help ensure they’re operating at the leading edge of API management, which will prove invaluable in a computing landscape that is poised to grow larger, more complex and more competitive over time.

Explore IBM API Connect

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