Comparing GraphQL Dataloader with Mongoose Populate

When it comes to performing a join-like operation, both GraphQL and Mongoose can be utilized for achieving the desired outcome.

Before posing any inquiries, consider the following example related to Task/Activities (please note that this code is purely for illustrative purposes and has not been tested):

Task {
  _id,
  title,
  description,
  activities: [{ //Of Activity Type
    _id,
    title
  }]
}

In Mongoose, you can fetch the activities associated with a task using the populate method, similar to this:

const task = await TaskModel.findbyId(taskId).populate('activities');

By employing GraphQL and Dataloader, a comparable result can be achieved as follows:

const DataLoader = require('dataloader');
const getActivitiesByTask = (taskId) => await ActivityModel.find({task: taskId});
const dataloaders = () => ({
    activitiesByTask: new DataLoader(getActivitiesByTask),
});
// ...
// SET The dataloader in the context
// ...

//------------------------------------------
// In another file
const resolvers = {
    Query: {
        Task: (_, { id }) => await TaskModel.findbyId(id),
    },
    Task: {
        activities: (task, _, context) => context.dataloaders.activitiesByTask.load(task._id),
    },
};

I attempted to search for an article comparing the performance and resource utilization of these two methods but came up empty-handed.

If you have any insights to share on this topic, your input would be greatly appreciated. Thank you!

Answer №1

It is crucial to understand that dataloaders serve as more than just a data model interface. While they are often described as a "streamlined and consistent API for various remote data sources," their true value in conjunction with GraphQL lies in the ability to incorporate caching and batching within a single request. This feature proves invaluable in APIs dealing with potentially duplicative data, such as retrieving user information along with their respective friends which could lead to redundant user queries.

In contrast, mongoose's populate function primarily acts as a means to aggregate multiple MongoDB requests. Therefore, attempting to compare these two functionalities is akin to comparing apples to oranges.

A fairer assessment would involve contrasting the use of populate demonstrated in your inquiry versus implementing a resolver for activities like so:

activities: (task, _, context) => Activity.find().where('id').in(task.activities)

The essential question then arises whether to load all the data in the parent resolver or distribute the workload across subsequent resolvers. It is worth noting that resolvers are only triggered for requested fields, signifying a notable performance disparity between these two approaches.

If the retrieval of the activities field is part of the query, both methods will entail a similar number of server-database interactions, resulting in marginal differences in performance. However, should the activities field be excluded from the request altogether, implementing a separate activities resolver can eliminate unnecessary database calls, optimizing efficiency.

Moreover...

Regarding MongoDB, aggregating queries using $lookup may prove less efficient than utilizing populate, as discussed here. Nevertheless, relational databases introduce additional factors to contemplate when evaluating these strategies. Leveraging joins during initial fetches in the parent resolver can significantly enhance query speed compared to individual database requests, albeit at the potential cost of slower no-activities-field queries.

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