TypeGraphQL VS dgraph

In this tutorial, we're building a simple application which uses Cerbos inside of a GraphQL server. The server is written in typescript and uses type-graphql to create the schema and resolvers, and TypeDI to handle dependency injection.

Using decorators required setting an --experimentalDecorators experimental compiler flag. Several popular TypeScript libraries, such as type-graphql and inversify, rely on this implementation.

TypeGraphQL

Have you tried TypeGraphQL v2 (it's in beta). Some in this thread have reported success with it.

When moving away from Apollo Server, and you're looking for a replacement built with JavaScript or TypeScript, let me give you some options. If you want to keep building your GraphQL API schema first, you might want to consider Mercurius (which relies on Fastify) or GraphQL Yoga. If you're going to build your GraphQL API code or resolver first, have a look at TypeGraphQL or Nexus. Alternatively, there are great GraphQL-as-a-Service solutions such as StepZen in case you no longer want to build, maintain and host your own GraphQL API.

There are two main approaches to keeping the types of the GraphQL schema and entities in business logic in sync. You can generate the schema based on your TypeScript code (e.g. TypeGraphQL), or you can generate types based on your schema (e.g. GraphQL Code Generator). We opted for the latter since it slotted right into our existing GraphQL server implementation using Apollo Server.

I've used tools (e.g. TypeGraphQL) in the past, and for smaller schemas I've just manually written the schema.

I'll be honest and say I don't think python is the right language to implement graphql. It's possible of course and if you're looking for a graphene tutorial, I'm sure you can find one (and I'll help you evaluate one, if you'd like). I'd personally go with node.js, typescript, and typegraphql.

Foal's dependencies have been updated so as to support the latest version of TypeGraphQL.

Dgraph: A distributed and scalable graph database known for high performance. It's a good fit for large-scale graph processing, offering a GraphQL-like query language and gRPC API support.

Dgraph (GraphQL, DQL)

Have you tried dgraph.io?

DGraph – A distributed GraphQL database with a graph backend.

How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic?

Consul Connect service mesh has a higher memory footprint, so on a small cluster with e5-medium nodes (2 vCPUs, 4 GB memory), you will only be able to support a maximum of 6 side-car proxies. In order to get an application like Dgraph working, which will have 6 nodes (3 Dgraph Alpha pods and 3 Dgraph Zero pods) for high availability along with at least one client, a larger footprint with more robust Kubernetes worker nodes were required.