graphql-spec VS dataloader

GraphQL's first draft release was 8 years ago. [1]

It's first non-draft release was 5 years ago. [2]

It's first release under a community foundation was 2 years ago. [3]

[1] https://spec.graphql.org/July2015/

[2] https://github.com/graphql/graphql-spec/releases/tag/June201...

[3] https://github.com/graphql/graphql-spec/releases/tag/October...

I'm a big believer in GraphQL (in fact, at time of writing I'm #2 contributor to the GraphQL spec itself) so it pains me that a tool I built doesn't always have easy ways to achieve the "versionless schema" design that GraphQL encourages when it comes to making significant breaking changes to your underlying database tables. (Personally, I think you should aim for your database schema itself to be versionless, but this is not always possible.) Of course you can build your PostGraphile schema over views instead of tables, but views have their own problems that I won't go into here…

I created a proposal for Map type but didn’t make it through.

https://github.com/graphql/graphql-spec/pull/888

The issue with GraphQL is it tries to appease too many masters.

Similar to jsx. The language isn’t evolving.

The good thing is the spec is (almost) frozen, so there’s many implementations, the bad is it can encompass the flexibility of json schema can do.

Longer thread - Subscriptions RFC: Are Subscriptions and Live Queries the same thing?

https://github.com/graphql/graphql-spec/issues/284

You’ve probably figured it out by now, but for others who may be in a similar position; GraphQL is a specification (with various implementations) and you can read up on the spec here: https://spec.graphql.org/

If you're asking whether GraphQL supports anonymous objects that can be arbitrarily nested then no, it doesn't.

show this feature request some love https://github.com/graphql/graphql-spec/issues/174

* Performance: It's just hard to track down what makes an operation slow. The waterfall nature of resolvers is a big contributor

[1] https://github.com/graphql/graphql-spec/issues/488

:::note GraphQL Union is available for Types only, not for Inputs. However, the oneOf directive will bridge the gap in the future.

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