The Workflow

1

Sequelize

To do this, try treating your resolvers as just entities which do an operation and respond back with data given a set of inputs (similar to what you would typically do with a REST API). So, try setting up your backend/datasources from which you would want to serve the data (be it a database like Postgres or Mongo with or without an ORM like Prisma, Knex or Sequelize, or even an underlying resource like a REST API maybe with something like GraphQL Mesh or Graph databases like Dgraph) and also your resolvers to process the data as you see fit, adding your business logic on top and return back the fields as needed by the resolvers. This is the point where you replace the mocked data with data from the backend.

#Development #Web Frameworks #Tool 44 social mentions

2

Redis

This is where you setup things like batching and also solve N+1 problems with something like a dataloader, setup caching with something like Redis or even an LRU cache to act as a proxy for the frequently accessed data whenever and wherever possible, optimizing the network chatter by using something like persisted queries, optimize your resolvers by retrieving as much data as possible from the parent resolvers, setting up pagination to limit the results returned, setting up things like query complexity to control the level of nesting and computation performed, rate-limiting in the gateway to avoid things like DDOS and so on.

#Key-Value Database #NoSQL Databases #Databases 183 social mentions

3

Prisma GraphQL API

To do this, try treating your resolvers as just entities which do an operation and respond back with data given a set of inputs (similar to what you would typically do with a REST API). So, try setting up your backend/datasources from which you would want to serve the data (be it a database like Postgres or Mongo with or without an ORM like Prisma, Knex or Sequelize, or even an underlying resource like a REST API maybe with something like GraphQL Mesh or Graph databases like Dgraph) and also your resolvers to process the data as you see fit, adding your business logic on top and return back the fields as needed by the resolvers. This is the point where you replace the mocked data with data from the backend.

#Project Management #Workflow Automation #Web Service Automation 63 social mentions

4

Mochajs

Testing plays a major role especially when building scalable systems which have to be reliable even with a huge stream of changes which might affect it over time. And this is no exception when you work with GraphQL as well. You can setup automated tests, integration tests and so on as you normally would to improve the confidence people have on the system. And there are lot of libraries which facilitate the same as well like Mocha, Jest, AVA and so on taking a lot of the burden away from you.

#Development Tools #Javascript UI Libraries #JavaScript Framework 86 social mentions

5

Knex.js

To do this, try treating your resolvers as just entities which do an operation and respond back with data given a set of inputs (similar to what you would typically do with a REST API). So, try setting up your backend/datasources from which you would want to serve the data (be it a database like Postgres or Mongo with or without an ORM like Prisma, Knex or Sequelize, or even an underlying resource like a REST API maybe with something like GraphQL Mesh or Graph databases like Dgraph) and also your resolvers to process the data as you see fit, adding your business logic on top and return back the fields as needed by the resolvers. This is the point where you replace the mocked data with data from the backend.

#Database Management #MySQL Tools #Databases 57 social mentions

6

Dgraph

To do this, try treating your resolvers as just entities which do an operation and respond back with data given a set of inputs (similar to what you would typically do with a REST API). So, try setting up your backend/datasources from which you would want to serve the data (be it a database like Postgres or Mongo with or without an ORM like Prisma, Knex or Sequelize, or even an underlying resource like a REST API maybe with something like GraphQL Mesh or Graph databases like Dgraph) and also your resolvers to process the data as you see fit, adding your business logic on top and return back the fields as needed by the resolvers. This is the point where you replace the mocked data with data from the backend.

#Graph Databases #Databases #NoSQL Databases 20 social mentions