apollo-angular VS dataloader

Case in point: Apollo Angular (GraphQL) does the basics of what you want, but it does so much more that its existence is justified...yet you still have to use RxJS with it.

Not that I know of. But here are a few things that may be of interest.

Redwood's GraphQL API is built on Yoga (we collaborate tightly with The Guild) — https://www.graphql-yoga.com You just need a GraphQL Client, which The Guild already has an option ready for you https://apollo-angular.com (Note: Apollo or other clients fine as well.)

Here's an example "How To" about connecting Next (React) with Redwood: https://community.redwoodjs.com/t/how-to-connect-a-next-js-f...

I'm a co-founder of Redwood and help lead the project so I can say as a matter of fact we a highly collaborative and enjoy (and support) exploratory projects. It's a priority for us to better demonstrate the power of Redwood's API through examples. If you'd be interested in digging in collaboratively with the community, I can help connect the dots. Just kick things off over here and tag me @thedavidprice: https://community.redwoodjs.com

No pressure at all! Just wanted you to know the invitation is open. Anytime.

Apollo Angular

TLDR: We’ve built a multiplayer shooter and used Apollo’s GraphQL subscriptions to keep game state in sync at a very high frequency. Here’s our impressions! Tools used: Angular-cesium, Apollo Angular, CesiumJS, Angular Go Play: geo-strike.com

When I began working with GraphQL, I had concerns about the N+1 query problem. In my research, I came across the DataLoader pattern and its implementation on GitHub. While I explored various examples of its usage, I still struggled to grasp how it operates internally. Join me in delving a bit deeper into GraphQL DataLoader! :)

DataLoader: it is the standard solution to N+1 problem.

Additionally, you can use DataLoader or similar tools to optimize data fetching and avoid over-fetching or under-fetching data. Ultimately, performance and load tests ensure that your GraphQL API delivers optimal performance, meets response time expectations, and provides a smooth experience for users, even under heavy loads.

The most common practice is to turn N+1 into 1+1 using dataloaders (https://github.com/graphql/dataloader for JS, there are equivalents for most implementations). The N resolvers invoke a single batched loader which receives a list of keys and returns a list of values.

Let's take Payload, for example. Surprise, surprise. We have a relationship field, and it can store IDs to other related documents which are seamlessly merged in when you retrieve documents from the DB. We leverage the dataloader pattern to batch together all "populations" required for a given query, returning them all super fast and with as few separate queries to the DB as possible. We actually even outperform SQL-based frameworks quite a bit. In a purely relational test, we were 3x faster than Directus and 7x faster than Strapi while both were running Postgres, and we were on MongoDB.

Also, have a look at Facebook's Dataloader[0].

[0] https://github.com/graphql/dataloader

In the next article, I'm going to implement a GraphQL server with dataloader using the tools we introduced.

The one example of using Scoped dependency that comes to my mind, it's HTTP request level caching for libs like dataloader.

you would fetch these 1000 rows via dataloader that batches all requests for this relation to a single query... solving the n+1 issue