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gRPC vs REST APIs — Key Differences
Application Programming Interfaces enable applications to access data or features of a service, operating system, or other applications. gRPC and REST are two common API specifications used to define the design of these interfaces.
This article compares gRPC vs REST as the two popular API frameworks, their benefits, limitations, and potential use-cases.
What is a REST API?
REST is an acronym for Representational State Transfer. It is an implementation of modern architectural styles that rely on a set of constraints to enable data exchange in hypermedia systems. Systems that obey REST constraints are referred to as RESTful.
A RESTful web API uses URL-encoded parameters to access resources using HTTP methods. The REST API framework has been widely adopted in modern web development for building stateless, scalable, and reliable APIs.
How does REST API work?
In a RESTful API, the client makes a request to a Uniform Resource Locator, which triggers a response whose payload is formatted in JSON, HTML, XML, or any other accepted data formats. This payload is a representation of the resource that the client requested. Client requests typically consist of
- A HTTP method that defines the operation to be performed on the resource
- A header that describes information about the resource request
- The resource path
- An optional message body with client data
REST APIs use HTTP verbs: GET, POST, PUT and DELETE, to perform resource Creation, Reading, Updating and Deletion (CRUD) operations. The client specifies the data formats they can receive within the Accept field within the header.
The API server sends a data payload to the requesting client, including a content-type header that specifies the message transmission format used in the response body. The response body also includes a response code that notifies the client about the success status of the API operation.
REST Features
Some design constraints that guide the building of REST APIs include:
Uniform interface
REST APIs are built to provide visibility for interactions between microservices. The design of a RESTful API calls for the application of the generality to the component interface for simpler overall architecture and observability. A uniform REST interface is achieved using four design constraints:
- The ability of each interface to uniquely identify all resources involved in interactions between the API client and the server.
- All resources should have uniform representations, which the API server can use to manipulate the resource state.
- Each representation should have detailed information describing how clients/servers can process the message body.
- The client should only access the initial application URI, using dynamic hyperlinks to access and manipulate resources.
Decoupling the client and the server
REST APIs enforce the separation of concerns by enabling the independent implementation of the client and the server. The code/programming language and implementation on the client side can be altered anytime without affecting how the server behaves and vice versa. So long as the client and server agree on the message transmission format, they can be kept modular and separate. The separation of client and server improves cross-platform interface flexibility by simplifying the development of server components. This decoupling also allows each component to evolve independently.
Stateless interface
RESTful APIs are stateless, meaning the server does not need to know the client’s state and vice versa. To achieve statelessness, each client request must contain all information the server needs to know about the resource and operation without seeing previous messages. The server should also respond with a message the client can completely understand without contextual information from previous session packets. Statelessness eliminates server load caused by storing previous requests and responses, making REST APIs reliable, fast and scalable.
Cacheability
Most API client machines and intermediaries can cache server responses. The API server response must define itself as cacheable or uncacheable when presented to the client. This prevents the API client from providing stale, cached data in response to further requests. Proper cache management streamlines client-server interactions by partially or totally eliminating some, further enhancing performance and scalability.
Layered architecture
The RESTful framework enforces the implementation of intermediary layers, such as proxies, which provide shared caches and load balancing capabilities. Intermediate layers enable the implementation of software development and management tools without updating the client-side or server-side code. With layered architecture, intermediate server components can call multiple other servers to create a response to a request without the client knowing whether it’s connected to the end server directly.
Code on demand
This is an optional constraint that allows the server to temporarily extend client functionality by downloading and executing code as scripts or java applets. This reduces the number of features that should be pre-implemented in client machines. The server delivers some of these features as scripts which the client executes.
What is gRPC?
gRPC is a universal, open-source, high-performance Remote Procedure Call (RPC) framework that enforces scalability and performance for microservice architecture. gRPC uses function calls to enforce client-server communication in microservices built with different programming languages. gRPC relies on the Interface Definition Language (IDL) to establish a contract/consensus on the data formats and functions to be called. gRPC APIs are implemented using the RPC model and HTTP 2.0 as the transport protocol.
How gRPC APIs Work
gRPC APIs rely on protocol buffers (protobufs), streaming, and the HTTP/2 protocol for message transmission. Protobuf is a serialization protocol that enables the auto-generation of client libraries and simple definition of microservices. API developers define services and messages between clients & servers in proto files. The files are loaded by the protoc compiler, which generates client and server code for exchanging messages with remote services. Messages encoded using protocol buffers are much smaller than XML or JSON representations, which makes parsing less CPU-intensive.
gRPC also uses HTTP/2, which introduces numerous upgrades to RPC architecture. The protocol introduces a binary framing layer that divides packets into smaller messages framed in binary format, making them compact and easily portable. HTTP/2 allows for multiple parallel requests with a bidirectional communication model, allowing for the implementation of multiple calls within a single channel.
While the HTTP/2 transport protocol allows for multiple simultaneous streams, gRPC extends this capability using channels. Each channel supports multiple simultaneous streams over varying concurrent connections. Channels provide a simple connection to the API server on a specific port and address. Channels are also used to create a client stub.
gRPC Features
Design constraints that guide the building of gRPC APIs include:
Resource & service-oriented design
gRPC promotes microservices architecture design and philosophy for loosely-coupled message exchange between systems to ensure efficient access for distributed objects. gRPC APIs are modeled as a resource hierarchy, with hosts being categorized into simple or collection resources. The resource-oriented design emphasizes the data model over the functionality implemented on resources; thus, the API exposes numerous resources with a small number of HTTP methods.
Open-source
When designing a gRPC API, development teams should make all the essential features free for public use. All API artifacts and components should be released as open source, using licensing terms that facilitate global adoption, not impede it.
Layered architecture
gRPC implements layered architecture with the base layer being the gRPC core layer. The other layers perform abstraction so that gRPC API developers don’t have to worry about the underlying details of RPC implementation. gRPC implements low-level communication details using code generated by Protobuf, and generates high-level abstractions for clients to work with.
Payload agnostic
Microservices use different encodings and message types, including JSON, XML, and protocol buffers. All API implementations must allow any microservice to use any message format to allow for easier message exchange and payload compression. The gRPC protocol and implementations should also support pluggable compression mechanisms to enforce performant message exchange across a broad class of use-cases.
Flow control
While the HTTP/2 protocol enables rapid exchange of messages across multiple channels, a lack of flow control can lead to traffic bottlenecks. Implementing stream-level and connection-level flow control enables the fine-grained control of memory used to buffer messages in transit. gRPC uses the WINDOW_UPDATE frame control, where both the server and client advertise the number of packets they can receive independently. The peer must respect the stated octet value, ensuring the receiver always has the buffering capacity for incoming messages.
Metadata exchange
Microservice management functions such as tracing, and authentication rely on the exchange of data that is not declared as part of a service interface. APIs should expose this data to ensure the services are performed seamlessly since the service declarative interface changes at a different rate to the data processed by these services.
Extensions as APIs
Software development teams that want to implement loosely-coupled interactions between services should consider using APIs in place of protocol extensions. These APIs can be used to build extensions for such functionalities as service introspection, load-balancing, load-monitoring, and health checks, among others.
Standard status codes
Clients have a specific set of ways to respond to API errors. To simplify error-handling decisions, error and status codes should be constrained and standardized. In larger deployments, developers can use the metadata exchange platform to provide a namespace for standardized status codes.
gRPC vs REST APIs — How They Differ
gRPC and REST APIs are built with different architectural styles to serve varying use-cases. This section compares the two API implementation styles based on various features and deployment aspects.
|-------------------|----------------------------|-----------------|
| Aspect | REST APIs | gRPC |
|-------------------|----------------------------|-----------------|
|Communication model|* Uses HTTP 1.1(or greater) |* Requires HTTP/2|
| |* Relies on requests and |* RPC-based with |
| |responses |capabilities for | | | |bidirectional |
| | |streaming | |-------------------|----------------------------|-----------------|
|Payload format |Mostly uses JSON with the |Uses Protobuf |
| |occasional HTML or XML |messages for |
| |message |serializing and | | | |encoding |
| | |structured data |
|-------------------|----------------------------|-----------------|
|Code generation |Developers requires a third |Ships with |
| |party tool like Swagger to |inbuilt code |
| |generate code for API |generation | | |requests |features |
| | | |
|-------------------|----------------------------|-----------------|
|Browser support |Enjoys universal browser |Needs gRPC-web |
| |support |+ a proxy to |
| | |convert between | | | |HTTP 1.1 and |
| | |HTTP 2, getting |
| | |restricted |
| | |browser support |
|-------------------|----------------------------|-----------------|
|Pros |* Simple learning curve |* Efficient |
| |* Ease of integration |parsing with |
| |* Better scalability |protocol buffers | | |* Resource efficiency |* Lightweight |
| | |messages | | | |* Inbuilt code |
| | |generation |
| | |* Provides more |
| | |options for |
| | |connection and |
| | |integration |
| | |*Offers better |
| | |streaming |
| | |capability |
| | |* Enhanced |
| | |security |
|-------------------|----------------------------|-----------------|
|Cons |* Lack of state |* Limited browser|
| |* Lacks confidentiality |support |
| | |* Steep learning | | | |curve |
| | |* Lacks edge |
| | |caching |
|-------------------|----------------------------|-----------------|REST vs gRPC APIs — When to Use
gRPC and REST APIs both find extensive use in modern, loosely-coupled, microservice-based application deployments.
REST APIs are built to connect microservice deployments that run both in-house and open-source resources since they offer numerous public integrations. REST APIs are best suited for applications requiring high-speed HTTP message transfer iteration. Since REST APIs use stateless calls, they are ideal for cloud applications that can accommodate flexible changes in workload.
Most third-party tools today lack innate gRPC API integration features, making gRPC ideal for building internal systems. gRPC can be used for lightweight microservice connections since Protobuf messages are highly portable. gRPC’s ability to handle multiplexing and two-way communications makes it suitable for real-time streaming in low-power, low-bandwidth connections.
Conclusion
The REST and gRPC API design models provide a way to connect loosely-coupled
Services in modern software development. This article has discussed the design principles guiding the development of APIs using both frameworks. It has also detailed a comparison based on development aspects, pros, and cons.
While REST APIs have dominated the cloud-native and microservice-based landscape, gRPC APIs offer innate security and portability, leading to rapid adoption within the past half-decade.
