Background
In the world of internet-driven information consumption, sluggish, and non-contextual internet response on requested information is a huge mood swinger. To solve this problem in web and mobile applications, in 2012, Facebook invented an alternative to the long prevalent REST API and called it GraphQL. GraphQL is a data query language that increases developer productivity and reduces the amount of data transferred in the API requests. After proving this advantage, Facebook open-sourced it in 2015 and since then it has been used by many companies like Github, New York Times, PayPal in application development.
Advantages of GraphQL
Universal data translation GraphQL has a huge positive implication on the developer community as a whole, because it removes errors between applications and servers, and helps incomplete data translation between various applications. This removes the bottleneck and pressure on the end application developers to ensure compatibility. Close to 100%, GraphQL requires an organized schema which in itself becomes a document.
Schema-based data definition Once the schema is defined, GraphQL considers it as a model with all the properties. It does not require to specify data requirements at the server-side and hence based on the schema data definition happens on the client-side. Thus, prototyping becomes much faster. This is apparent from the fact that emerging product companies are relying on GraphQL.
Rapid product development GraphQL is a boon to front end developers. The GraphQL libraries allow for realtime updates on the UI without touching the backend and therefore, iterations on app development are fast. Without GraphQL, it would have required longer than usual and an entire team to deliver the same. GraphQL facilitates schema driven development which means features are designed as per the schema created on the server. GraphQL APIs can be stitched together and therefore a single API can be developed from an existing API. This reduces the complexity to deal with multiple endpoints. Schema stitching also makes the API re-usable, thereby shortening the product development time.
Enhance backend stability Stability comes from the simplicity with which GraphQL structures the data, independent of the client requests. GraphQL acts like a translatable layer between the client and the server which directs the server data requests to the necessary resources and systems. This allows modifications in the application backend, without restructuring the client. Since the data is passed in the language path itself, the query looks simple and elegant. Stability is further achieved because GraphQL defines the shape of the objects returned by the API.
Improved query efficiency GraphQL gives the application developer a single entry point for multiple queries instead of multiple or ad hoc endpoints and complex data retrievals. The data is defined in a schema on the server, it is delivered in a single predictable package rather than differentiated packets. The software developers don’t have to rely on the REST endpoints which return pre-defined and fixed data structures. Pre-defined data structures lead to either getting more information than needed, called over fetching, or getting less information than needed, called under fetching, in a single query. Underfetching and Overfetching are two commonly observed problems in the REST APIs. Schema-based data on the server, adds predictability to the APIs output. GraphQL decreases the number of resources required in each data query. Servers are able to publish contextual output in the APIs and the client can request the data with simple data calls. This means the application developers can implement data restrictions naturally with minimal impact on consumers. GraphQL improves queuing efficiency as it adds specificity and predictability in the output which improves the product development speed. This type of query output also reduces the load on the backend, which need not be modified every time there is an iteration in the product development. Read More about : Api automation testing
Tags: API Testing, Postman, REST API, Swagger
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