Bridging Frontend and Backend with GraphQL and Apache Kafka ft. Gerard Klijs | Streaming Audio: Apache Kafka® & Real-Time Data podcast

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Episode description

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Episode description

What is GraphQL? And how can you combine GraphQL with Apache Kafka® to query data in real time?

With over 10 years of experience as a backend engineer, Gerard Klijs is a Confluent Community Catalyst, a contributor to several GraphQL libraries, and also a creator and maintainer of a Rust library to use Confluent Schema Registry with Java client. In this episode, he explains why you want to use Kafka with GraphQL and how they work together to bridge the gap between backend and frontend to make data more easily accessible in the frontend.

As an alternative to REST, GraphQL is an open source programming language developed by Meta, which lets you pull data from multiple data sources via a single API call. GraphQL lets you migrate and deprecate data easily. For example, if you have a `name` field, which you later decided to replace by `firstName` and `lastName`, you can group the field names together and monitor the server for query requests. If there are no additional query requests for the deprecated field, then it can be removed from the server.

Usually, GraphQL is used in the frontend with a server implemented in Node.js, while Kafka is often used as an integration layer between backend components. When it comes to connecting Kafka with GraphQL, the use cases might not seem as vast at first glance, but Gerard thinks that it is due to unfamiliarity and misconceptions on how the two can work together. For example, some may think Kafka is merely a message bus and GraphQL is for graph databases.

Gerard also talks about the backend for frontend (BFF) pattern as well as tips on working with GraphQL.

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