Guide to Super Graph

Without writing a line of code get an instant high-performance GraphQL API for your Ruby-on-Rails app. Super Graph will automatically understand your apps database and expose a secure, fast and complete GraphQL API for it. Built in support for Rails authentication and JWT tokens.


  • Works with Rails database schemas
  • Automatically learns schemas and relationships
  • Belongs-To, One-To-Many and Many-To-Many table relationships
  • Full text search and Aggregations
  • Rails Auth supported (Redis, Memcache, Cookie)
  • JWT tokens supported (Auth0, etc)
  • Highly optimized and fast Postgres SQL queries
  • Configure with a simple config file
  • High performance GO codebase
  • Tiny docker image and low memory requirements

Try it out

# download super graph source
git clone

# setup the demo rails app & database
./demo setup

# run the demo
./demo run

# signin to the demo app ( / 123456)
open http://localhost:3000

# try the super graph web ui
open http://localhost:8080


This demo requires docker you can either install it using brew or from the docker website

Trying out GraphQL

We currently support the query action which is used for fetching data. Support for mutation and subscriptions is work in progress. For example the below GraphQL query would fetch two products that belong to the current user where the price is greater than 10

GQL Query

query {
  users {
    picture : avatar
    products(limit: 2, where: { price: { gt: 10 } }) {

The above GraphQL query returns the JSON result below. It handles all kinds of complexity without you having to writing a line of code.

For example there is a while greater than gt and a limit clause on a child field. And the avatar field is renamed to picture. The password field is blocked and not returned. Finally the relationship between the users table and the products table is auto discovered and used.

JSON Result

  "data": {
    "users": [
        "id": 1,
        "email": "",
        "picture": "",
        "full_name": "Edwin Orn",
        "products": [
            "id": 16,
            "name": "Sierra Nevada Style Ale",
            "description": "Belgian Abbey, 92 IBU, 4.7%, 17.4°Blg",
            "price": 16.47

Try with an authenticated user

In development mode you can use the X-User-ID: 4 header to set a user id so you don't have to worries about cookies etc. This can be set using the HTTP Headers tab at the bottom of the web UI you'll see when you visit the above link. You can also directly run queries from the commandline like below.

Querying the GQL endpoint

# fetch the response json directly from the endpoint using user id 5
curl 'http://localhost:8080/api/v1/graphql' \
  -H 'content-type: application/json' \
  -H 'X-User-ID: 5' \
  --data-binary '{"query":"{ products { name price users { email }}}"}'

How to GraphQL

GraphQL (GQL) is a simple query syntax that's fast replacing REST APIs. GQL is great since it allows web developers to fetch the exact data that they need without depending on changes to backend code. Also if you squint hard enough it looks a little bit like JSON 😃

The below query will fetch an users name, email and avatar image (renamed as picture). If you also need the users id then just add it to the query.

query {
  user {
    picture : avatar

Fetching data

To fetch a specific product by it's ID you can use the id argument. The real name id field will be resolved automatically so this query will work even if your id column is named something like product_id.

query {
  products(id: 3) {

Postgres also supports full text search using a TSV index. Super Graph makes it easy to use this full text search capability using the search argument.

query {
  products(search "amazing") {

Complex queries (Where)

Super Graph support complex queries where you can add filters, ordering,offsets and limits on the query.

Logical Operators

Name Example Explained
and price : { and : { gt: 10.5, lt: 20 } price > 10.5 AND price < 20
or or : { price : { greater_than : 20 }, quantity: { gt : 0 } } price >= 20 OR quantity > 0
not not: { or : { quantity : { eq: 0 }, price : { eq: 0 } } } NOT (quantity = 0 OR price = 0)

Other conditions

Name Example Explained
eq, equals id : { eq: 100 } id = 100
neq, not_equals id: { not_equals: 100 } id != 100
gt, greater_than id: { gt: 100 } id > 100
lt, lesser_than id: { gt: 100 } id < 100
gte, greater_or_equals id: { gte: 100 } id >= 100
lte, lesser_or_equals id: { lesser_or_equals: 100 } id <= 100
in status: { in: [ "A", "B", "C" ] } status IN ('A', 'B', 'C)
nin, not_in status: { in: [ "A", "B", "C" ] } status IN ('A', 'B', 'C)
like name: { like "phil%" } Names starting with 'phil'
nlike, not_like name: { nlike "v%m" } Not names starting with 'v' and ending with 'm'
ilike name: { ilike "%wOn" } Names ending with 'won' case-insensitive
nilike, not_ilike name: { nilike "%wOn" } Not names ending with 'won' case-insensitive
similar name: { similar: "%(b|d)%" } Similar Docs
nsimilar, not_similar name: { nsimilar: "%(b|d)%" } Not Similar Docs
has_key column: { has_key: 'b' } Does JSON column contain this key
has_key_any column: { has_key_any: [ a, b ] } Does JSON column contain any of these keys
has_key_all column: [ a, b ] Does JSON column contain all of this keys
contains column: { contains: [1, 2, 4] } Is this array/json column a subset of value
contained_in column: { contains: "{'a':1, 'b':2}" } Is this array/json column a subset of these value
is_null column: { is_null: true } Is column value null or not

Aggregation (Max, Count, etc)

You will often find the need to fetch aggregated values from the database such as count, max, min, etc. This is simple to do with GraphQL, just prefix the aggregation name to the field name that you want to aggregrate like count_id. The below query will group products by name and find the minimum price for each group. Notice the min_price field we're adding min_ to price.

query {
  products {
Name Explained
avg Average value
count Count the values
max Maximum value
min Minimum value
stddev Standard Deviation
stddev_pop Population Standard Deviation
stddev_samp Sample Standard Deviation
variance Variance
var_pop Population Standard Variance
var_samp Sample Standard variance

All kinds of queries are possible with GraphQL. Below is an example that uses a lot of the features available. Comments # hello are also valid within queries.

query {
    # returns only 30 items
    limit: 30,

    # starts from item 10, commented out for now
    # offset: 10,

    # orders the response items by highest price
    order_by: { price: desc },

    # no duplicate prices returned
    distinct: [ price ]

    # only items with an id >= 30 and < 30 are returned
    where: { id: { and: { greater_or_equals: 20, lt: 28 } } }) {

Using variables

Variables ($product_id) and their values ("product_id": 5) can be passed along side the GraphQL query. Using variables makes for better client side code as well as improved server side SQL query caching. The build-in web-ui also supports setting variables. Not having to manipulate your GraphQL query string to insert values into it makes for cleaner and better client side code.

// Define the request object keeping the query and the variables seperate
var req = { 
  query: '{ product(id: $product_id) { name } }' ,
  variables: { "product_id": 5 }

// Use the fetch api to make the query
fetch('http://localhost:8080/api/v1/graphql', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify(req),
.then(res => res.json())
.then(res => console.log(;

Every app these days needs search. Enought his often means reaching for something heavy like Solr. While this will work why add complexity to your infrastructure when Postgres has really great and fast full text search built-in. And since it's part of Postgres it's also available in Super Graph.

query {
    # Search for all products that contain 'ale' or some version of it
    search: "ale"

    # Return only matches where the price is less than 10
    where: { price: { lt: 10 } }

    # Use the search_rank to order from the best match to the worst
    order_by: { search_rank: desc }) {

This query will use the tsvector column in your database table to search for products that contain the query phrase or some version of it. To get the internal relevance ranking for the search results using the search_rank field. And to get the highlighted context within any of the table columns you can use the search_headline_ field prefix. For example search_headline_name will return the contents of the products name column which contains the matching query marked with the <b></b> html tags.

  "data": {
    "products": [
        "id": 11,
        "name": "Maharaj",
        "search_rank": 0.243171,
        "search_headline_description": "Blue Moon, Vegetable Beer, Willamette, 1007 - German <b>Ale</b>, 48 IBU, 7.9%, 11.8°Blg"
        "id": 12,
        "name": "Schneider Aventinus",
        "search_rank": 0.243171,
        "search_headline_description": "Dos Equis, Wood-aged Beer, Magnum, 1099 - Whitbread <b>Ale</b>, 15 IBU, 9.5%, 13.0°Blg"

Adding search to your Rails app

It's really easy to enable Postgres search on any table within your database schema. All it takes is to create the following migration. In the below example we add a full-text search to the products table.

class AddSearchColumn < ActiveRecord::Migration[5.1]
  def self.up
    add_column :products, :tsv, :tsvector
    add_index :products, :tsv, using: "gin"

    say_with_time("Adding trigger to update the ts_vector column") do
      execute <<-SQL
        CREATE FUNCTION products_tsv_trigger() RETURNS trigger AS $$
          new.tsv :=
          setweight(to_tsvector('pg_catalog.english', coalesce(,'')), 'A') ||
          setweight(to_tsvector('pg_catalog.english', coalesce(new.description,'')), 'B');
          return new;
        $$ LANGUAGE plpgsql;

        CREATE TRIGGER tsvectorupdate BEFORE INSERT OR UPDATE ON products FOR EACH ROW EXECUTE PROCEDURE products_tsv_trigger();

  def self.down
    say_with_time("Removing trigger to update the tsv column") do
      execute <<-SQL
        DROP TRIGGER tsvectorupdate
        ON products

    remove_index :products, :tsv
    remove_column :products, :tsv


You can only have one type of auth enabled. You can either pick Rails or JWT.

Rails Auth (Devise / Warden)

Almost all Rails apps use Devise or Warden for authentication. Once the user is authenticated a session is created with the users ID. The session can either be stored in the users browser as a cookie, memcache or redis. If memcache or redis is used then a cookie is set in the users browser with just the session id.

Super Graph can handle all these variations including the old and new session formats. Just enable the right auth config based on how your rails app is configured.

  type: rails
  cookie: _app_session

    # Rails version this is used for reading the
    # various cookies formats.
    version: 5.2

    # Found in 'Rails.application.config.secret_key_base'
    secret_key_base: 0a248500a64c01184edb4d7ad3a805488f8097ac761b76aaa6c17c01dcb7af03a2f18ba61b2868134b9c7b79a122bc0dadff4367414a2d173297bfea92be5566

Memcache session store

  type: rails
  cookie: _app_session

    # Memcache remote cookie store.
    url: memcache://

Redis session store

  type: rails
  cookie: _app_session

    # Redis remote cookie store
    url: redis://
    password: ""
    max_idle: 80
    max_active: 12000

JWT Token Auth

  type: jwt

    # the two providers are 'auth0' and 'none'
    provider: auth0 
    secret: abc335bfcfdb04e50db5bb0a4d67ab9
    public_key_file: /secrets/public_key.pem
    public_key_type: ecdsa #rsa

For JWT tokens we currently support tokens from a provider like Auth0 or if you have a custom solution then we look for the user_id in the subject claim of of the id token. If you pick Auth0 then we derive two variables from the token user_id and user_id_provider for to use in your filters.

We can get the JWT token either from the authorization header where we expect it to be a bearer token or if cookie is specified then we look there.

For validation a secret or a public key (ecdsa or rsa) is required. When using public keys they have to be in a PEM format file.

Easy to setup

Configuration files can either be in YAML or JSON their names are derived from the GO_ENV variable, for example GO_ENV=prod will cause the prod.yaml config file to be used. or GO_ENV=dev will use the dev.yaml. A path to look for the config files in can be specified using the -path <folder> command line argument.

We're tried to ensure that the config file is self documenting and easy to work with.

app_name: "Super Graph Development"
web_ui: true
debug_level: 1

# enabling tracing also disables query caching
enable_tracing: true

# Throw a 401 on auth failure for queries that need auth
# valid values: always, per_query, never
auth_fail_block: never

# Postgres related environment Variables

# Auth related environment Variables

# inflections:
#   person: people
#   sheep: sheep

  # Can be 'rails' or 'jwt'
  type: rails
  cookie: _app_session

  # Comment this out if you want to disable setting
  # the user_id via a header. Good for testing
  header: X-User-ID

    # Rails version this is used for reading the
    # various cookies formats.
    version: 5.2

    # Found in 'Rails.application.config.secret_key_base'
    secret_key_base: 0a248500a64c01184edb4d7ad3a805488f8097ac761b76aaa6c17c01dcb7af03a2f18ba61b2868134b9c7b79a122bc0dadff4367414a2d173297bfea92be5566

    # Remote cookie store. (memcache or redis)
    # url: redis://
    # password: test
    # max_idle: 80,
    # max_active: 12000,

    # In most cases you don't need these
    # salt: "encrypted cookie"
    # sign_salt: "signed encrypted cookie"
    # auth_salt: "authenticated encrypted cookie"

  # jwt:
  #   provider: auth0
  #   secret: abc335bfcfdb04e50db5bb0a4d67ab9
  #   public_key_file: /secrets/public_key.pem
  #   public_key_type: ecdsa #rsa

  type: postgres
  host: db
  port: 5432
  dbname: app_development
  user: postgres
  password: ''
  # pool_size: 10
  # max_retries: 0
  # log_level: "debug"

  # Define variables here that you want to use in filters
    account_id: "select account_id from users where id = $user_id"

  # Define defaults to for the field key and values below
    filter: ["{ user_id: { eq: $user_id } }"]

    # Fields and table names that you wish to block
      - ar_internal_metadata
      - schema_migrations
      - secret
      - password
      - encrypted
      - token

    - name: users
      # This filter will overwrite defaults.filter
      filter: ["{ id: { eq: $user_id } }"]

    - name: products
      # Multiple filters are AND'd together
      filter: [
        "{ price: { gt: 0 } }",
        "{ price: { lt: 8 } }"

    - name: customers
      # No filter is used for this field not
      # even defaults.filter
      filter: none

    - # You can create new fields that have a
      # real db table backing them
      name: me
      table: users
      filter: ["{ id: { eq: $user_id } }"]

    # - name: posts
    #   filter: ["{ account_id: { _eq: $account_id } }"]

If deploying into environments like Kubernetes it's useful to be able to configure things like secrets and hosts though environment variables therfore we expose the below environment variables. This is escpecially useful for secrets since they are usually injected in via a secrets management framework ie. Kubernetes Secrets

Keep in mind any value can be overwritten using environment variables for example auth.jwt.public_key_type converts to SG_AUTH_JWT_PUBLIC_KEY_TYPE. In short prefix SG_, upper case and all . should changed to _.

Postgres environment variables


Auth environment variables


Developing Super Graph

If you want to build and run Super Graph from code then the below commands will build the web ui and launch Super Graph in developer mode with a watcher to rebuild on code changes. And the demo rails app is also launched to make it essier to test changes.

# yarn is needed to build the web ui
brew install yarn

# yarn install dependencies and build the web ui
(cd web && yarn install && yarn build)

# generate some stuff the go code needs
go generate ./...

# do this the only the time to setup the database
docker-compose run web rake db:create db:migrate

# start super graph in development mode with a change watcher
docker-compose up

MIT License

MIT Licensed | Copyright © 2018-present Vikram Rangnekar