Benchmarking GraphQL Node.js Servers

Benchmarking GraphQL Node.js Servers

Learn how to improve the performance of your GraphQL Node.js servers. Includes using graphql-jit, avoiding apollo-trace, and swapping apollo-server out for express-graphql

Learn how to improve the performance of your GraphQL Node.js servers. Includes using graphql-jit, avoiding apollo-trace, and swapping apollo-server out for express-graphql


Creating a simple CRUD app with NodeJS, GraphQL and React

Creating a simple CRUD app with NodeJS, GraphQL and React

Make CRUD simple with Node, GraphQL, and React. GraphQ Lreduces the complexity of building APIs by abstracting all requests to a single endpoint. Unlike traditional REST APIs, it is declarative; whatever is requested is returned

GraphQL reduces the complexity of building APIs by abstracting all requests to a single endpoint. Unlike traditional REST APIs, it is declarative; whatever is requested is returned.

Of course, not all projects require GraphQL — it is merely a tool to consolidate data. It has well-defined schema, so we know for sure we won’t overfetch. But if we already have a stable RESTful API system where we rely on data from a single data source, we don’t need GraphQL.

For instance, let’s assume we are creating a blog for ourselves and we decide to store, retrieve, and communicate to data in a single MongoDB database. In this case, we are not doing anything architecturally complex, and we don’t need GraphQL.

On the other hand, let’s imagine we have a full-fledged product that relies on data from multiple sources (e.g., MongoDB, MySQL, Postgres, and other APIs). In this case, we should go for GraphQL.

For example, if we’re designing a portfolio site for ourselves and we want data from social media and GitHub (to show contributions), and we also have our own database to maintain a blog, we can use GraphQL to write the business logic and schema. It will consolidate data as a single source of truth.

Once we have the resolver functions to dispatch the right data to the front end, we will easily be able to manage data within a single source. In this article, we’re going to implement simple end-to-end CRUD operations with GraphQL.

CRUD with graphql-server

Setting up our server

We are going to spin off a simple GraphQL server using express-graphql and get it connected to a MySQL database. The source code and the MySQL files are in this repository.

A GraphQL server is built on top of schema and resolvers. As a first step, we build a schema (defining types, queries, mutations, and subscriptions). This schema describes the whole app structure.

Secondly, for the stuff defined in the schema, we’re building respective resolvers to compute and dispatch data. A resolver maps actions with functions; for each query declared in typedef, we create a resolver to return data.

Finally, we complete server settings by defining an endpoint and passing configurations. We initialize /graphql as the endpoint for our app. To the graphqlHTTP middleware, we pass the built schema and root resolver.

Along with the schema and root resolver, we’re enabling the GraphiQL playground. GraphiQL is an interactive in-browser GraphQL IDE that helps us play around with the GraphQL queries we build.

var express = require('express');
var graphqlHTTP = require('express-graphql');
var { buildSchema } = require('graphql');

var schema = buildSchema(`
  type Query {
    hello: String

var root = {
  hello: () => "World"

var app = express();

app.use('/graphql', graphqlHTTP({
  schema: schema,
  rootValue: root,
  graphiql: true,


console.log('Running a GraphQL API server at localhost:4000/graphql');

Once the server is good to go, running the app with node index.js will start the server on http://localhost:4000/graphql. We can query for hello and get the string “World” as a response.

Connecting the database

I’m going to establish the connection with the MySQL database as shown below:

var mysql = require('mysql');

app.use((req, res, next) => {
  req.mysqlDb = mysql.createConnection({
    host     : 'localhost',
    user     : 'root',
    password : '',
    database : 'userapp'

We can connect multiple databases/sources and get them consolidated in the resolvers. I’m connecting to a single MySQL database here. The database dump I’ve used for this article is in the GitHub repository.

Reading and writing data with GraphQL

We use queries and mutations to read and modify data in data-sources. In this example, I’ve defined a generic queryDB function to help query the database.


All the SELECT statements (or read operations) to list and view data goes into the type Query typedef. We have two queries defined here: one to list all the users in the database, and another to view a single user by id.

  1. Listing data: To list users, we’re defining a GraphQL schema object type called User, which represents what we can fetch or expect from the getUsers query. We then define the getUsers query to return an array of users.
  2. Viewing a single record: To view a single record, we’re taking id as an argument with the getUserInfo query we have defined. It queries for that particular id in the database and returns the data to the front end.

Now that we have put together the queries to fetch all records and to view record by id, when we try to query for users from GraphiQL, it will list an array of users on the screen! 🙂

var schema = buildSchema(`
  type User {
    id: String
    name: String
    job_title: String
    email: String
  type Query {
    getUsers: [User],
    getUserInfo(id: Int) : User

const queryDB = (req, sql, args) => new Promise((resolve, reject) => {
    req.mysqlDb.query(sql, args, (err, rows) => {
        if (err)
            return reject(err);
        rows.changedRows || rows.affectedRows || rows.insertId ? resolve(true) : resolve(rows);

var root = {
  getUsers: (args, req) => queryDB(req, "select * from users").then(data => data),
  getUserInfo: (args, req) => queryDB(req, "select * from users where id = ?", []).then(data => data[0])


The write operations for the database — CREATE, UPDATE, DELETE — are generally defined under mutations. The mutations are executed in a sequential manner by the GraphQL engine. Queries are executed parallelly.

  1. Creating data: We have defined a mutation, createUser, that takes the specified arguments to create data in the MySQL database.
  2. Updating or deleting data: Similar to viewing a record, update (updateUserInfo) and delete (deleteUser) take id as a param and modify the database.

The functions resolve with a boolean to indicate whether the change happened or not.

var schema = buildSchema(`
  type Mutation {
    updateUserInfo(id: Int, name: String, email: String, job_title: String): Boolean
    createUser(name: String, email: String, job_title: String): Boolean
    deleteUser(id: Int): Boolean

var root = {
  updateUserInfo: (args, req) => queryDB(req, "update users SET ? where id = ?", [args,]).then(data => data),
  createUser: (args, req) => queryDB(req, "insert into users SET ?", args).then(data => data),
  deleteUser: (args, req) => queryDB(req, "delete from users where id = ?", []).then(data => data)

Now that we have set and sorted the server side of things, let’s try and connect the back end to our React app.

CRUD with graphql-client

Once we have the server in place, creating client logic to display and mutate data is easy. Apollo Client helps in state management and caching. It is also highly abstracted and quick: all of the logic for retrieving your data, tracking loading and error states, and updating UI is encapsulated by the useQuery Hook.

Connecting to graphql-server

I have created a CRA boilerplate and have installed GraphQL, apollo-boost, and @apollo/react-hooks. We initialize Apollo Client and get it hooked to React.

import React from 'react';
import ReactDOM from 'react-dom';
import App from './App';
import ApolloClient from 'apollo-boost';
import { ApolloProvider } from '@apollo/react-hooks';

const client = new ApolloClient({
  uri: 'http://localhost:4000/graphql'

  <ApolloProvider client={client}>
    <App />

Reading and mutating data

I have managed all the GraphQL queries in the Queries folder of my source code. I’m going to request data from the server with the useQuery Hook, which is built on top of the React Hooks API. It helps in bringing in data into the UI.

GraphQL queries are generally wrapped in the gql function. gql helps convert query string into a query document. Here’s how we define queries in our app.

import { gql } from 'apollo-boost';

export const GET_USERS = gql`
    getUsers {

export const VIEW_USERS = gql`
  query ($id: Int){
    getUserInfo(id: $id) {

export const ADD_USER = gql`
  mutation($name: String, $email: String, $job_title: String) {
    createUser (name: $name, email: $email, job_title: $job_title)

export const EDIT_USER = gql`
  mutation($id: Int, $name: String, $email: String, $job_title: String) {
    updateUserInfo (id: $id, name: $name, email: $email, job_title: $job_title)

export const DELETE_USER = gql`
  mutation($id: Int) {
    deleteUser(id: $id)

Once ApolloProvider is set, we can request data from our GraphQL server. We pass the query we are trying to make to the useQuery Hook, and it will provide the result for us.

I’ve made two queries, with and without arguments, to show how we should be handling queries and mutations in the front end. useQuery tracks error and loading states for us and will be reflected in the associated object. Once the server sends the result, it will be reflected by the data property.

import React from 'react';
import { useQuery } from '@apollo/react-hooks';
import { GET_USERS, VIEW_USERS } from "./Queries";
import { Card, CardBody, CardHeader, CardSubtitle, Spinner } from 'reactstrap';

function App() {
  const getAllUsers = useQuery(GET_USERS);
  const userInfo = useQuery(VIEW_USERS, { variables: { id: 1 }});
  if (getAllUsers.loading || userInfo.loading) return <Spinner color="dark" />;
  if (getAllUsers.error || userInfo.error) return <React.Fragment>Error :(</React.Fragment>;

  return (
    <div className="container">
        <CardHeader>Query - Displaying all data</CardHeader>
            {JSON.stringify(, null, 2)}
        <CardHeader>Query - Displaying data with args</CardHeader>
          <CardSubtitle>Viewing a user by id</CardSubtitle>
            {JSON.stringify(, null, 2)}

export default App;

Similar to querying, mutations will use the same useQuery Hook and will pass data as variables into the query.

const deleteMutation = useQuery(DELETE_USER, { variables: { id: 8 }});
const editMutation = useQuery(EDIT_USER, { variables: { id: 9, name: "Username", email: "email", job_title: "job" }});
const createMutation = useQuery(ADD_USER, { variables: { name: "Username", email: "email", job_title: "job" }});

Monitor Failed and Slow GraphQL Requests in Production

While GraphQL has some features for debugging requests and responses, making sure GraphQL continues to serve resources to your app in production is where things get tougher. If you’re interested in ensuring requests to the backend or 3rd party services are successful,

LogRocket is like a DVR for web apps, recording literally everything that happens on your site. Instead of guessing why problems happen, you can aggregate and report on problematic GraphQL requests to quickly understand the root cause.

LogRocket instruments your app to record baseline performance timings such as page load time, time to first byte, and slow network requests as well as logs Redux, NgRx. and Vuex actions/state. Start monitoring for free.


Ta-da! We just did end-to-end CRUD operations with GraphQL. On the client side, reading and mutating data has become very simple after the introduction of React Hooks. Apollo Client also provides provisions for authentication, better error handling, caching, and optimistic UI.

Subscriptions is another interesting concept in GraphQL. With this application as boilerplate, we can keep experimenting with other concepts like these!

Happy coding!

Node.js for Beginners - Learn Node.js from Scratch (Step by Step)

Node.js for Beginners - Learn Node.js from Scratch (Step by Step)

Node.js for Beginners - Learn Node.js from Scratch (Step by Step) - Learn the basics of Node.js. This Node.js tutorial will guide you step by step so that you will learn basics and theory of every part. Learn to use Node.js like a professional. You’ll learn: Basic Of Node, Modules, NPM In Node, Event, Email, Uploading File, Advance Of Node.

Node.js for Beginners

Learn Node.js from Scratch (Step by Step)

Welcome to my course "Node.js for Beginners - Learn Node.js from Scratch". This course will guide you step by step so that you will learn basics and theory of every part. This course contain hands on example so that you can understand coding in Node.js better. If you have no previous knowledge or experience in Node.js, you will like that the course begins with Node.js basics. otherwise if you have few experience in programming in Node.js, this course can help you learn some new information . This course contain hands on practical examples without neglecting theory and basics. Learn to use Node.js like a professional. This comprehensive course will allow to work on the real world as an expert!
What you’ll learn:

  • Basic Of Node
  • Modules
  • NPM In Node
  • Event
  • Email
  • Uploading File
  • Advance Of Node

Building a GraphQL API with Node, Express and MongoDB

Building a GraphQL API with Node, Express and MongoDB

Create a GraphQL API With Node.js, Mongoose, and Express .This quick-and-dirty tutorial is just the beginning of all the fun you can have using GraphQL to make your development stronger, cleaner, and more efficient.

GraphQL is a technology that helps developers build robust software more quickly. The ability to request all of the information you need in a single request is a game changer.

It has simplified the back-end development of APIs for consumption by mobile and web applications that would normally rely on RESTful APIs. A normal RESTful API may have several end points for various entities (e.g., users, submissions, etc.); with GraphQL, you can get all of this information in a single go using GraphQL’s query language, also known as GQL.

In this tutorial, I’ll walk you through how to build a GraphQL API with graphql-compose-mongoose, as well as a few other tools. And, of course, everything will be to ES6 spec using Node.js. If this sounds like an exciting adventure, read on.

Getting Started

To get started, we’ll need to double-check you have a few prerequisites to ensure both that you understand the technology and that you can complete the tutorial in full.


  • Node.js (Latest 13.x or above)
  • Yarn (brew install yarn on macOS)
  • An understanding of JavaScript and the ES6 spec
  • An account with MongoDB Atlas or a local instance of MongoDB running
Directory Structure

To start, create a new directory.

You can name your directory whatever you would like; for this tutorial, we’re going to create a to-do application, so I called mine todo.

mkdir todo && cd todo

Next, let’s go ahead and generate our package.json file using Yarn. We’ll add modules, as necessary, as we continue to move forward.

yarn init


Note: Answer the questions as prompted. Nothing necessarily required here — just whatever you’d like to set as your defaults.

Because we are using ES6, we’ll need to transpile all code from ES6 to vanilla JavaScript. To do so, let’s go ahead and create a src directory. Note that we’ll also need to set up the required structure within the src. The script below will accomplish the following:

  • Make a src directory
  • Move into the src directory
  • Generate schema, models, scripts, and utils directories
mkdir src && cd src && mkdir models schema scripts utils

Lastly, we’ll create an index.js file, which will allow us to import our dependent files and directories:

touch index.js

Inside of index.js, place the following contents, and save:

import dotenv from 'dotenv';
import express from 'express';
import { ApolloServer } from 'apollo-server-express';

import mongoose from 'mongoose';

import './utils/db';
import schema from './schema';


const app = express();

const server = new ApolloServer({
    cors: true,
    playground: process.env.NODE_ENV === 'development' ? true : false,
    introspection: true,
    tracing: true,
    path: '/',

    path: '/',
    cors: true,
    onHealthCheck: () =>
        // eslint-disable-next-line no-undef
        new Promise((resolve, reject) => {
            if (mongoose.connection.readyState > 0) {
            } else {

app.listen({ port: process.env.PORT }, () => {
    console.log(`🚀 Server listening on port ${process.env.PORT}`);
    console.log(`😷 Health checks available at ${process.env.HEALTH_ENDPOINT}`);


Package File

Now that we have the base files in place, let’s go ahead and add the required production packages to our package.json file using Yarn, like so:

yarn add @babel/cli @babel/core @babel/node @babel/preset-env apollo-engine apollo-server-express body-parser cors dotenv express graphql graphql-compose graphql-compose-connection graphql-compose-mongoose graphql-middleware graphql-tools mongoose mongoose-bcrypt mongoose-timestamp

And for development packages, add the following:

yarn add --dev babel-eslint babel-loader babel-preset-env eslint eslint-plugin-babel eslint-plugin-import eslint-plugin-node eslint-plugin-promise fs-extra nodemon prettier

Now that we have the necessary packages installed, we can modify our package.json file to allow for additional functionality.

Let’s modify it to add scripts and hooks; once we’ve done that, your package.json file should look much like this:


The below will allow us to run scripts via Yarn (e.g., yarn <INSERT SCRIPT HERE>). For example, we can lint our code using yarn lint, and it’ll perform ESLint and Prettier operations on our files.

"scripts": {
    "build": "babel src --out-dir dist",
    "start": "node dist/index.js",
    "dev": "nodemon --exec npx babel-node src/index.js",
    "prettier": "prettier --config ./.prettierrc --write \"**/*.js\"",
    "pretest": "eslint --ignore-path .gitignore .",
    "postinstall": "rm -rf dist && yarn run build",
    "lint": "yarn prettier --write --check --config ./.prettierrc \"**/*.js\" && eslint --fix ./src",
    "release": "release-it patch --no-npm.publish"


Similar to above, we’ll add a Husky script that will trigger on the precommit event, effectively running yarn lint for us prior to committing code.

This is an excellent practice for maintaining quality, clean code:

"husky": {
    "hooks": {
        "pre-commit": "yarn lint"


That’s all for scripts. Let’s continue on.

Configuring Babel, Prettier, and ESLint

We’ve taken the necessary steps to install the correct packages for Babel, Prettier, and ESLint.

Now, it’s time to add the configuration files to the root of your project. Move the root, and add the following files:


    "presets": [
                "targets": {
                    "node": "current"



    "trailingComma": "es5",
    "tabWidth": 4,
    "semi": true,
    "singleQuote": true



    "plugins": ["babel"],
    "extends": ["eslint:recommended"],
    "rules": {
        "no-console": 0,
        "no-mixed-spaces-and-tabs": 1,
        "comma-dangle": 0,
        "no-unused-vars": 1,
        "eqeqeq": [2, "smart"],
        "no-useless-concat": 2,
        "default-case": 2,
        "no-self-compare": 2,
        "prefer-const": 2,
        "object-shorthand": 1,
        "array-callback-return": 2,
        "valid-typeof": 2,
        "arrow-body-style": 2,
        "require-await": 2,
        "react/prop-types": 0,
        "no-var": 2,
        "linebreak-style": [2, "unix"],
        "semi": [1, "always"]
    "env": {
        "node": true
    "parser": "babel-eslint",
    "parserOptions": {
        "sourceType": "module",
        "ecmaVersion": 2018,
        "ecmaFeatures": {
            "modules": true


Perfect! We’re making progress.

Onto the next section.

Creating Our Models

The reason I enjoy working with graphql-compose-mongoose is that it allows me to use Mongoose models rather than writing GraphQL models by hand (which, by the way, can become quite cumbersome on a large application).

Head over to src/models, and create a new file named user.js. Inside this file, we’ll define all of the required characteristics that make up a user. This will be a small file, but feel free to add additional information to the user record if you wish (for example, a password using mongoose-bcrypt).

import mongoose, { Schema } from 'mongoose';
import timestamps from 'mongoose-timestamp';
import { composeWithMongoose } from 'graphql-compose-mongoose';

export const UserSchema = new Schema(
        name: {
            type: String,
            trim: true,
            required: true,
        email: {
            type: String,
            lowercase: true,
            trim: true,
            unique: true,
            required: true,
        collection: 'users',


UserSchema.index({ createdAt: 1, updatedAt: 1 });

export const User = mongoose.model('User', UserSchema);
export const UserTC = composeWithMongoose(User);


Next, let’s create a task.js file (given that this is, after all, a to-do GraphQL API):

import mongoose, { Schema } from 'mongoose';
import timestamps from 'mongoose-timestamp';
import { composeWithMongoose } from 'graphql-compose-mongoose';

export const TaskSchema = new Schema(
        user: {
            type: Schema.Types.ObjectId,
            ref: 'User',
            required: true,
        task: {
            type: String,
            trim: true,
            required: true,
        description: {
            type: String,
            trim: true,
            required: true,
        collection: 'tasks',


TaskSchema.index({ createdAt: 1, updatedAt: 1 });

export const Task = mongoose.model('Task', TaskSchema);
export const TaskTC = composeWithMongoose(Task);


We now have two models/schemas: UserSchema and TaskSchema.

A user is an individual entity, and a task always belongs to a user. From this, we will eventually be able to pull all tasks for a user in a single GraphQL call. Pretty cool, right?

Creating Our Schemas

Schemas are an interesting part of this implementation. They, essentially, allow us to define what calls can and cannot be made to the server.

Schemas are made up of queries and mutations, where queries allow you to fetch data, and mutations allow you to modify data. Let’s create our schemas for both the user and task model.

Inside of the schema directory, create a file called user.js. Then, drop the following contents into the file:

import { User, UserTC } from '../models/user';

const UserQuery = {
    userById: UserTC.getResolver('findById'),
    userByIds: UserTC.getResolver('findByIds'),
    userOne: UserTC.getResolver('findOne'),
    userMany: UserTC.getResolver('findMany'),
    userCount: UserTC.getResolver('count'),
    userConnection: UserTC.getResolver('connection'),
    userPagination: UserTC.getResolver('pagination'),

const UserMutation = {
    userCreateOne: UserTC.getResolver('createOne'),
    userCreateMany: UserTC.getResolver('createMany'),
    userUpdateById: UserTC.getResolver('updateById'),
    userUpdateOne: UserTC.getResolver('updateOne'),
    userUpdateMany: UserTC.getResolver('updateMany'),
    userRemoveById: UserTC.getResolver('removeById'),
    userRemoveOne: UserTC.getResolver('removeOne'),
    userRemoveMany: UserTC.getResolver('removeMany'),

export { UserQuery, UserMutation };


Next, let’s create one called task.js:

import { Task, TaskTC } from '../models/task';

const TaskQuery = {
    taskById: TaskTC.getResolver('findById'),
    taskByIds: TaskTC.getResolver('findByIds'),
    taskOne: TaskTC.getResolver('findOne'),
    taskMany: TaskTC.getResolver('findMany'),
    taskCount: TaskTC.getResolver('count'),
    taskConnection: TaskTC.getResolver('connection'),
    taskPagination: TaskTC.getResolver('pagination'),

const TaskMutation = {
    taskCreateOne: TaskTC.getResolver('createOne'),
    taskCreateMany: TaskTC.getResolver('createMany'),
    taskUpdateById: TaskTC.getResolver('updateById'),
    taskUpdateOne: TaskTC.getResolver('updateOne'),
    taskUpdateMany: TaskTC.getResolver('updateMany'),
    taskRemoveById: TaskTC.getResolver('removeById'),
    taskRemoveOne: TaskTC.getResolver('removeOne'),
    taskRemoveMany: TaskTC.getResolver('removeMany'),

export { TaskQuery, TaskMutation };


To tie things together, we’ll generate an index.js file in the root of the directory (src/schema) and import our schemas:

import { SchemaComposer } from 'graphql-compose';

import db from '../utils/db'; // eslint-disable-line no-unused-vars

const schemaComposer = new SchemaComposer();

import { UserQuery, UserMutation } from './user';
import { TaskQuery, TaskMutation } from './task';



export default schemaComposer.buildSchema();


Now that we have full CRUD capabilities with GraphQL, let’s add our final utilities.

Build Script

The build script allows you to transform your Mongoose-style schemas into pure GraphQL schemas. Pretty fancy, huh?

Create a file called buildSchema.js inside of src/scripts, and drop the following code in:

import fs from 'fs-extra';
import path from 'path';
import { graphql } from 'graphql';
import { introspectionQuery, printSchema } from 'graphql/utilities';

import Schema from '../schema';

async function buildSchema() {
    await fs.ensureFile('../data/schema.graphql.json');
    await fs.ensureFile('../data/schema.graphql');

        path.join(__dirname, '../data/schema.graphql.json'),
        JSON.stringify(await graphql(Schema, introspectionQuery), null, 2)

        path.join(__dirname, '../data/schema.graphql.txt'),

async function run() {
    await buildSchema();
    console.log('Schema build complete!');

run().catch(e => {


This file will be called with the yarn build command and will output the raw GraphQL queries into a data directory.

Database Connectivity

What’s an API without a database? That’s why we’ll need to create a connection from Mongoose to MongoDB.

If you haven’t already created a .env file in the root directory, now’s the time to do so. You’ll want to ensure it has the following environment variables:



Once your .env file’s in place, let’s go ahead and create another file inside of src/utils. Name the file db.js, and add the following contents:

import mongoose from 'mongoose';
import dotenv from 'dotenv';


mongoose.Promise = global.Promise;

const connection = mongoose.connect(process.env.MONGODB_URI, {
    autoIndex: true,
    reconnectTries: Number.MAX_VALUE,
    reconnectInterval: 500,
    poolSize: 50,
    bufferMaxEntries: 0,
    keepAlive: 120,
    useNewUrlParser: true,

mongoose.set('useCreateIndex', true);

    .then(db => db)
    .catch(err => {

export default connection;


Note: If you don’t have MongoDB up and running locally, MongoDB Atlas is a great alternative. Not only is it free, but it packs enough power on the free tier to run a development application without any issues. Check it out here.

The Playground

Your GraphQL is now complete. Run the command yarn dev, and you’ll be able to spin up the playground for GraphQL, which allows you to add, modify, remove, and query users and tasks — all in one call.

It looks a little something like this:


This quick-and-dirty tutorial is just the beginning of all the fun you can have using GraphQL to make your development stronger, cleaner, and more efficient.

Try expanding on what you’ve just built to add additional functionality to the models, or venture out on your own to improve one of your existing applications — or even spin up a new one; I’d love to hear more about all that you decide to do.

Until then, thank you for following me along throughout this tutorial, and stay tuned for future updates. Happy coding!