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Grpc vs rest api performance7/30/2023 ![]() additionally, pipelining has been found very difficult to deploy, because many intermediaries and servers don't process it correctly. Http/1.1 tried to fix this with pipelining, but it didn't completely address the problem (a large or slow response can still block others behind it). Http/1.x has a problem called "head-of-line blocking," where effectively only one request can be outstanding on a connection at a time. Http/2 is fully multiplexed, instead of ordered and blocking Our response time reduces from 15 ms to 1.71 ms for each request, where average requests ranges from 600 rpm to 1700 rpm.First, let's look at some of the high-level differences:īinary protocols are more efficient to parse, more compact "on the wire," and, most importantly, they are much less error-prone compared to textual protocols like http/1.x, because they often have a number of affordances to "help" with things like whitespace handling, capitalization, line endings, blank lines, and so on.ĭefines four different ways to parse a message in To conclude, APIs created with gRPC gives us incredible performance improvement as compared to legacy REST API. Other synchronous messaging technologies such as RESTful services and GraphQL are more suitable for external-facing services. Therefore, as a general practice, we can use it for all synchronous communications between internal microservices. It used in those use cases where there is a requirement of communication between services internally. Second option is to create one Microservice using REST which can deal with external services and rest of services deal with each other internally through gRPC. ![]() It is only available for internal services because there is no APIs available for external use, but the Google team is working on gRPC-web also so that users can also use this for external services communications. Multiplexing, full duplex, proto request/response makes gRPC much faster as compared to REST. But it can be used only in those use cases where there is internal communication between services. This makes the process very slow, memory-consuming and non-compressible. REST APIs communicate with each other with payloads like JSON, XML and many more. If any of the services is slow, then it will affect all the system because REST does not support features like multiplexing, duplex streaming. One service calls either one service or two services or maybe more services and further those services may be calling other services. Initially, all micro-services were interconnected through REST APIs.
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