Grpc vs rest api performance code#
Based on a Protobuf contract, gRPC generates compatible client and server code in chosen programming languages. To define the contracts, gRPC uses a declarative language called Protocol Buffers (Protobuf). GRPC is contract-based: a contract needs to be available on both sides of communication to make sense of data going between them.
Before being open sourced in 2016, gRPC has evolved from Google’s internal infrastructure where it connected a plethora of large-scale services running across data centers. GRPC is Google’s current implementation of the tried and tested RPC (Remote Procedure Call) paradigm where each request is structured like a function call in a programming language. As solid as Roy Fielding’s doctoral dissertation is, it can’t serve as a specification, and developers tend to interpret REST in different ways. Teams that need to increase efficiency of data transfer via REST often end up creating more and more endpoints. JSON:API’s sparse fieldsets) that allow filtering data in the response, but these workarounds have their own tradeoffs, such as in terms of cacheability. There’s also potential for overfetching where if the client only needs a specific piece of data, it will nevertheless receive all the data that the requested endpoint is configured to return.In addition, using HTTP/2 helps alleviate this problem by reducing handshakes and allowing better compression. Workarounds are available, most prominently the notion of “compound documents” in JSON:API. REST is prone to underfetching: if you have nested entities - for example, you want to get users along with their comments, - you may need to make multiple requests.If you want to send an email, it’s hard to do in a RESTful way as there’s no resource to act upon.
REST is not a great fit for domains where mapping concepts to resources is hard.This ambiguity has led the community to create more specific, opinionated frameworks like JSON:API, HAL, and OData.
Grpc vs rest api performance how to#
It doesn’t give you predefined answers to common questions like how to name resources, format JSON requests, include related resources, or implement paging. REST is a broad architectural style, as opposed to a concrete API framework or specification, and it leaves a lot of room for interpretation. REST requires requests to be cacheable whenever possible, and caching is implemented using HTTP’s native caching headers. When the client makes a request, it includes all information necessary for the server to process that request, and resends the information with subsequent requests if needed. REST is stateless - the server never stores the client’s state. It uses URLs to address resources and HTTP verbs ( GET, POST, PUT, DELETE, PATCH) to express the action to take. REST aims to follow HTTP semantics closely. REST can be defined as a stateless, cacheable, convention-based architecture for client-server interaction. REST was described way back in 2000 in Roy Fielding’s doctoral dissertation as the core architectural principle of the World Wide Web. REST (REpresentational State Transfer) is the most mature of the 3 API technology options.
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