😎 Components all the way down - A better GraphQL implementation!

β€” 3 minute read

I have recently introduced the β€œschemaless” GraphQL, which is based on the PoP API. In this post, I will write about the improvements that using the component-based architecture can achieve over a typical schema-based implementation of GraphQL.

Improved Speed and Safety permalink

The time complexity to execute queries is much lower: Whereas GraphQL's is exponential (O(2^n)), PoP's is just quadratic (or O(n^2)) in worst case, and linear (or O(n)) in average (where n is the amount of nodes in the query graph). As a consequence, executing deeply nested queries will take lower time, and the risk of Denial of Service attacks is also reduced.

Support for Public/Private API, One-Graph solution for everything permalink

Because the schema is dynamically built from a component model, it can decide to incorporate or discard different elements based on different factors or situations. As such, these use cases can be easily implemented:

Make an API that is both public and private, by enabling certain fields only if the user is logged-in, or if the user has a specific user role (such as admin)

Build a One-Graph solution for everything, creating a customizable gateway to different services (Twitter, Salesforce, Slack, Stripe, etc) from a single endpoint

Field-based Cache-control permalink

Through a special directive, each field can indicate its cache-control configuration, and the request will calculate the overall cache-control based on all the requested fields:

  • If any field cannot be cached (such as those with user state), then the request is not cached
  • Otherwise, the request is cached using the lowest value

Decentralization permalink

GraphQL's schema requires a type definition to live on a single location, making it difficult for team members to collaborate, often leading to a monolith architecture, or to the need to set-up special tooling to generate the schema.

Because PoP is schemaless, it overcomes these drawbacks, and supports:

  • Cleanly splitting the data model into different responsibilities (implemented by different, disconnected teams), without the need to set-up special tooling
  • Deprecation of fields based on the needs from the team/project, not on the API schema definition
  • Overriding of field resolvers (eg: to test new features or provide quick fixes)

Check out these examples:

Normal behaviour:
?query=posts.id|title|excerpt

Overriding behaviour #1 (available under the "experimental" branch):
?query=posts.id|title|excerpt(branch:experimental,length:30)

Overriding behaviour #2 (available under the "try-new-features" branch):
?query=posts(limit:2).id|title|content|content(branch:try-new-features,project:block-metadata)

Federation, coming soon permalink

Imagine that you need to implement the following functionality:

  • In some system, you have a REST API endpoint returning the subscribers to a newsletter: a list of email and lang fields

  • In another system, you have a database with user information: rows of id, email and name fields

  • In another system, you have blog posts

  • You want to send the content of a blog post in a newsletter to all your users, like this:

    Hi {name},

    welcome to our weekly newsletter! Our post from today:

    {post-title}

    {post-content}

  • The newsletter must be translated to the user's preferred language!

How would you do that using a standard GraphQL implementation? Would you believe me if I say that, through the schemaless GraphQL, this can be resolved in only 1 line, and without implementing any custom server-side code?

πŸ€”

I will keep you posted πŸ€”