David Adegoke Well known for his skills and dynamic leadership, David has led development teams building and deploying great products. He is passionate about helping people learn mobile development with Flutter and the leadership strategies they need to succeed regardless of their background. As he says, "You just have to be consistent and intentional to make it."

tRPC vs. GraphQL: Which is better for your projects?

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tRPC vs. GraphQL: Which is better for your projects?

Building robust and efficient APIs is a critical aspect of software development, and choosing the right API technology is paramount to delivering fast, reliable, and secure API services.

When choosing an API technology, you’ll want to consider factors such as the complexity of your project, the number of endpoints you’ll need, the expected traffic, and the client requirements. It’s also important to consider the skills and experience of your development team, as some technologies may require a steeper learning curve than others.

In this article, we’ll compare tRPC and GraphQL and highlight their pros and cons to help you decide which API technology best suits your project.

Jump ahead:

What is tRPC?

tRPC is an open source remote procedure call (RPC) framework that is fast, lightweight, and enables efficient communication between client and server applications. It simplifies building high-performance and scalable APIs by automating many everyday tasks required for API development over HTTP/2.

tRPC uses Protocol Buffers as its default serialization format for encoding and decoding the data that is transferred between the client and server across multiple languages and technology stacks.

How tRPC works

tRPC automates data serialization and deserialization between client and server, allowing you to define API methods and request/response data in a simple, readable syntax. This way, when clients make requests, you don’t have to worry about the low-level details. tRPC also provides automatic code generation for clients and servers.

tRPC is language agnostic, and you can build clients and servers that support Protocol Buffers, including Go, Java, Python, and Node.js.

Notable tRPC features

Several features of tRPC make the API technology attractive for building scalable and performant APIs. Here are some of the features:

  • Protocol Buffers: tRPC uses Protocol Buffers as its data serialization format
  • Automatic code generation: tRPC provides automatic code generation for both the client and server, which eliminates the need to write boilerplate code, saving time and reducing potential errors
  • HTTP/2 support: tRPC supports HTTP/2, a significant improvement over HTTP/1.1 in performance and scalability. HTTP/2 supports multiplexed requests and responses that allow efficient use of network resources
  • Streaming support: tRPC supports bidirectional streaming, which lets you simulate real-time communication between the client and server, and is helpful for applications that require real-time updates, like chat applications or real-time dashboards

Why you should use tRPC

tRPC is an excellent option for building robust and efficient web apps. The primary reasons why you’ll want to use tRPC as the API technology for your app include its ease of use and its performance and scalability.

You can get up and running with tRPC in minutes because of its simple and intuitive API, and its efficient binary protocol for communication boosts its performance and scalability. This makes tRPC ideal for applications that need to handle high-traffic requests.

Drawbacks of using tRPC

While there are many benefits of using tRPC, you must be aware of some cons of using tRPC.

tRPC has a complex configuration process that can be challenging for beginners. While experienced developers may find the configuration process easy, it may discourage some developers from getting started using tRPC.

Another significant limitation of tRPC is its limited language support. tRPC doesn’t support other popular languages like Java, Ruby, and Python, which is a challenge to widespread adoption. tRPC also has limited framework support. It works well with a few web frameworks like Next.js and Express.js, but it may differ too much to be useful with other frameworks like Django, Spring, or Laravel.

Integrating tRPC into existing projects that use unsupported frameworks can also add extra development time and complexity, which reduces its performance benefits. Despite these limitations, tRPC is still an excellent option for specific projects, such as large-scale web applications that require complex APIs.

Suitable projects for tRPC

tRPC’s performance and scalability make it an ideal choice for high-traffic projects that require efficient client-server communication. TypeScript projects can also easily be built with tRPC because it itself it built using TypeScript, so it integrates seamlessly into TypeScript projects.

Finally, tRPC is an excellent option for projects requiring many API calls. The framework’s performance and efficiency make it an ideal choice for projects that rely heavily on APIs.

What is GraphQL?

GraphQL is a query language and runtime for APIs that revolutionizes how we build APIs on HTTP. GraphQL provides a more efficient, powerful, and flexible way of building APIs than traditional REST APIs.

GraphQL enables clients to precisely specify and receive only the data they need, reducing the amount of data transfer over the network and improving performance. Unlike REST APIs, where complex applications have many endpoints for data consumption, GraphQL APIs have one entry point for everything.

How GraphQL works

GraphQL solves the issues of over-fetching and under-fetching, which is an issue with traditional APIs. By fetching only requested data, clients can reduce resources, leading to better performance for their use case.

GraphQL APIs have a schema written in its own schema definition language (SDL) that consists of types and fields. You can fetch all the data in a GraphQL API by describing what you want with a single query. Types define the shape of the data and its fields, and the fields represent the data you can query.

When clients query a GraphQL API, the server validates the query against the schema. If the query is valid, the server processes the query and returns the requested data as a JSON object. The response will match the structure of the query, making it easy for clients to understand and operate on the data.

Notable GraphQL features

GraphQL owes its growing adoption to its wide array of features. Here are some notable features of GraphQL:

  • Strong type system: GraphQL’s robust type system enables developers to define data types and queries, validate the data structure, simplify finding errors, improve performance by reducing unnecessary data transfer, and ensure data consistency across your application
  • Flexible querying: GraphQL offers a flexible query system that eliminates the problem of over-fetching and under-fetching. When the client specifies the data requirements in the query, the server returns only the requested data, resulting in faster response times and improved performance
  • Real-time data with subscriptions: GraphQL supports real-time data updates using subscriptions that can push data to the client as soon as it changes on the server. Subscriptions are especially useful for building applications that require live updates, like chat applications and stock market dashboards
  • Interoperation with existing systems: GraphQL integrates with myriad existing systems, which makes it easy to adopt GraphQL without having to rewrite your entire application
  • Simple API layer: GraphQL provides a simple and consistent API layer that abstracts the complexity of underlying systems and makes it easier to maintain and manage applications

Why you should use GraphQL

GraphQL stands out from other API technologies for three reasons:

  • Efficient data transfer and flexibility
  • Great developer experience
  • Easy to learn

GraphQL’s efficient data transfer method reduces what gets transferred over a network. In traditional RESTful APIs, the client has to make multiple requests to complex APIs to fetch all the data it needs.

Additionally, GraphQL is flexible; with the right query, you can fetch the exact data you need without over or under-fetching data. GraphQL‘s ’robust typing system also ensures the client and server agree on the data structure, reducing errors and increasing code reliability.

GraphQL’s excellent developer experience also makes it easy to learn and use. The GraphQL SDL is easy to understand, and many resources are available online to help you get started. It provides functionality for automatic API documentation, so that consumers can easily understand your API without consulting external documentation.

Automatic documentation generation eases the process of developing and maintaining APIs.

Drawbacks of using GraphQL

GraphQL sacrifices a few features for the benefits it provides. One of these is caching: since GraphQL allows clients to request exact data, it isn’t easy to cache responses relative to traditionally REST APIs. You can cache data at the endpoint level with REST; for GraphQL, you’ll have to cache at the field level, which may be challenging to implement.

Another drawback is GraphQL’s complexity. GraphQL increases the complexity of your application’s backend because it is more flexible than traditional REST APIs. On top of this, exact data fetching makes query optimization difficult, which can be taxing while developing complex applications.

Suitable projects for GraphQL

GraphQL is an excellent choice for developing mobile and web applications that require flexibility and efficiency. GraphQL APIs are consistent and predictable, so they’re easy to maintain over time.

GraphQL is handy for building microservices, where several services interact and interoperate. With GraphQL, you can compose single APIs from multiple APIs into a unified interface that’s easy to update.

GraphQL is a great option for ecommerce, IoT, and real-time apps because it’s easy to scale and can interact with the large amounts of data from different sources these apps tend to process.

Comparing tRPC and GraphQL

As we’ve discussed, tRPC and GraphQL are both modern API technologies that excel at the operations they’re designed for.

tRPC is mainly used for building performant microservices, while GraphQL is used for building flexible APIs for efficient data transfer between web and mobile applications.

Here’s a table that compares the API technologies:


Category tRPC GraphQL
Protocol type Remote procedure call (RPC) Query language
Server implementation Node.js, Go, etc. Node.js, Java, Python, Ruby, etc.
Client implementation JavaScript, TypeScript, Dart, Swift, Kotlin, etc. JavaScript, TypeScript, Dart, Swift, Kotlin, etc.
Transport protocols HTTP/2, gRPC, WebSocket HTTP/1.1, HTTP/2, WebSocket
Request/response format Protocol Buffers, JSON, MessagePack JSON
Type system Strongly typed, supports both scalar and custom types Strongly typed, supports both scalar and custom types
Schema language TypeScript GraphQL SDL (Schema Definition Language)
Querying Single request/response per method call Batched queries/mutations, allowing multiple queries/mutations. Executable in a single request/response
Subscriptions Built-in support for real-time data updates Built-in support for real-time data updates
Performance Faster than GraphQL, due to the use of binary serialization and multiplexing Slower than tRPC, due to the use of text-based serialization and batching
Ecosystem Still growing, but has good community support Has a large and mature ecosystem, with many tools and libraries available
Learning curve Steeper than GraphQL, due to the use of TypeScript and fewer available learning resources Less steep than tRPC, due to its popularity and abundance of available learning resources

Overall, tRPC and GraphQL are both powerful API technologies, but tRPC is faster and better suited for low-latency, high-throughput applications, while GraphQL is more flexible and better suited for building APIs that need to support a wide range of clients and use cases.

Your choice between tRPC and GraphQL ultimately depends on the specific needs of your project and the trade-offs you’re willing to take.


Hurray! You’ve learned about tRPC and GraphQL, their features, their pros and cons, and the projects for which they’re best suited.

Both tRPC and GraphQL have their strengths and weaknesses. Ultimately, the choice between tRPC and GraphQL depends on your project’s specific requirements and your development team’s skills and experience.

If you have any questions, please contact me via social media. I’ll be glad to assist and answer any questions. Til I write to you again, happy coding.

Monitor failed and slow GraphQL requests in production

While GraphQL has some features for debugging requests and responses, making sure GraphQL reliably serves resources to your production app is where things get tougher. If you’re interested in ensuring network requests to the backend or third party services are successful, try LogRocket.LogRocket Dashboard Free Trial Bannerhttps://logrocket.com/signup/

LogRocket is like a DVR for web and mobile apps, recording literally everything that happens on your site. Instead of guessing why problems happen, you can aggregate and report on problematic GraphQL requests to quickly understand the root cause. In addition, you can track Apollo client state and inspect GraphQL queries' key-value pairs.

LogRocket instruments your app to record baseline performance timings such as page load time, time to first byte, slow network requests, and also logs Redux, NgRx, and Vuex actions/state. Start monitoring for free.
David Adegoke Well known for his skills and dynamic leadership, David has led development teams building and deploying great products. He is passionate about helping people learn mobile development with Flutter and the leadership strategies they need to succeed regardless of their background. As he says, "You just have to be consistent and intentional to make it."

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