FireSQL - Query Firestore using SQL syntax

What is FireSQL?

FireSQL is a library built on top of the official Firebase SDK that allows you to query Cloud Firestore using SQL syntax. It's smart enough to issue the minimum amount of queries necessary to the Firestore servers in order to get the data that you request.

On top of that, it offers some of the handy utilities that you're used to when using SQL, so that it can provide a better querying experience beyond what's offered by the native querying methods.

Installation

Just add firesql and firebase to your project:

``sh
npm install firesql firebase


or


yarn add firesql firebase
`

If you want to receive realtime updates when querying, then you will also need to install rxjs and rxfire:

`sh
npm install firesql firebase rxjs rxfire


or


yarn add firesql firebase rxjs rxfire
`

Usage

`js
// You can either query the collections at the root of the database...
const dbRef = firebase.firestore();

// ... or the subcollections of some document
const docRef = firebase.firestore().doc('someDoc');

// And then just pass that reference to FireSQL
const fireSQL = new FireSQL(dbRef);

// Use .query() to get a one-time result
fireSQL.query('SELECT * FROM myCollection').then(documents => {
documents.forEach(doc => {
/ Do something with the document /
});
});

// Use .rxQuery() to get an observable for realtime results.
// Don't forget to import "firesql/rx" first (see example below).
fireSQL.rxQuery('SELECT * FROM myCollection').subscribe(documents => {
/ Got an update with the documents! /
});

`

Examples

$3

`js
import { FireSQL } from 'firesql';
import firebase from 'firebase/app';
import 'firebase/firestore';

firebase.initializeApp({ / ... / });

const fireSQL = new FireSQL(firebase.firestore());

const citiesPromise = fireSQL.query(
SELECT name AS city, country, population AS people
FROM cities
WHERE country = 'USA' AND population > 700000
ORDER BY country, population DESC
LIMIT 10
);

citiesPromise.then(cities => {
for (const city of cities) {
console.log(
${city.city} in ${city.country} has ${city.people} people
);
}
});
`

$3

`js
import { FireSQL } from 'firesql';
import firebase from 'firebase/app';
import 'firesql/rx'; // <-- Important! Don't forget
import 'firebase/firestore';

firebase.initializeApp({ / ... / });

const fireSQL = new FireSQL(firebase.firestore());

const cities$ = fireSQL.rxQuery(
SELECT city, category, AVG(price) AS avgPrice
FROM restaurants
WHERE category IN ("Mexican", "Indian", "Brunch")
GROUP BY city, category
);

cities$.subscribe(results => {
/ REALTIME AGGREGATED DATA! /
});
`

Limitations

- Only SELECT queries for now. Support for INSERT, UPDATE, and DELETE might come in the future.
- No support for JOINs.
- LIMIT doesn't accept an OFFSET, only a single number.
- No support for aggregate function COUNT.
- If using GROUP BY, it cannot be combined with ORDER BY nor LIMIT.
- No support for negating conditions with NOT.
- Limited LIKE. Allows for searches in the form of WHERE field LIKE 'value%', to look for fields that begin with the given value; and WHERE field LIKE 'value', which is functionally equivalent to WHERE field = 'value'.

Nested objects


You can access nested objects by using backticks around the field path. For example, if you have a collection "products" with documents like this:
`js
{
productName: "Firebase Hot Sauce",
details: {
available: true,
stock: 42
}
}
`
You could do the following queries:
`sql
SELECT *
FROM products
WHERE details.stock > 10
`
`sql
SELECT productName, details.stock AS productStock
FROM products
WHERE details.available = true
`

Getting the document IDs

You can use the special field __name__ to refer to the document ID (its key inside a collection). For convenience, you might want to alias it:
`sql
SELECT __name__ AS docId, country, population
FROM cities
`

If you always want to include the document ID, you can specify that as a global option to the FireSQL class:
`js
const fireSQL = new FireSQL(ref, { includeId: true}); // To include it as "__name__"
const fireSQL = new FireSQL(ref, { includeId: 'fieldName'}); // To include it as "fieldName"
`

You can also specify that option when querying. This will always take preference over the global option:
`js
fireSQL.query(sql, { includeId: 'id'}); // To include it as "id"
fireSQL.query(sql, { includeId: false}); // To not include it
`

When querying it's also possible to use the document as a search field by using __name__ directly. For example, you could search for all the documents whose IDs start with Hello:
`sql
SELECT *
FROM cities
WHERE __name__ LIKE 'Hello%'
`

> Note: You will need to specify the includeId option if you want to obtain the document IDs when doing a SELECT * query.

Collection group queries

You can easily do collection group queries with FireSQL!

This query will get all documents from any collection or subcollection named "landmarks":
`sql
SELECT *
FROM GROUP landmarks
`

You can read more about collection group queries in the official Firestore documentation.

Array membership queries


It's as simple as using the CONTAINS condition:
`sql
SELECT *
FROM posts
WHERE tags CONTAINS 'interesting'
`

You can read more about array membership queries in the official Firestore documentation.

How does FireSQL work?

FireSQL transforms your SQL query into one or more queries to Firestore. Once all the necessary data has been retrieved, it does some internal processing in order to give you exactly what you asked for.

For example, take the following SQL:
`sql
SELECT *
FROM cities
WHERE country = 'USA' AND population > 50000
`
This would get transformed into this single Firestore query:
`js
db.collection('cities')
.where('country', '==', 'USA')
.where('population', '>', 50000);
`
That's pretty straightforward. But what about this one?
`sql
SELECT *
FROM cities
WHERE country = 'USA' OR population > 50000
`
There's no direct way to perform an OR query on Firestore so FireSQL splits that into 2 separate queries:
`js
db.collection('cities').where('country', '==', 'USA');
db.collection('cities').where('population', '>', 50000);
`
The results are then merged and any possible duplicates are eliminated.

The same principle applies to any other query. Sometimes your SQL will result in a single Firestore query and some other times it might result in several.

For example, take a seemingly simple SQL statement like the following:
`sql
SELECT *
FROM cities
WHERE country != 'Japan' AND region IN ('north', 'east', 'west') AND (capital = true OR population > 100000)
`

This will need to launch a total of 12 concurrent queries to Firestore!
`js
const cities = db.collection('cities');
cities.where('country', '<', 'Japan').where('region', '==', 'north').where('capital', '==', true);
cities.where('country', '<', 'Japan').where('region', '==', 'north').where('population', '>', 100000);
cities.where('country', '<', 'Japan').where('region', '==', 'east').where('capital', '==', true);
cities.where('country', '<', 'Japan').where('region', '==', 'east').where('population', '>', 100000);
cities.where('country', '<', 'Japan').where('region', '==', 'west').where('capital', '==', true);
cities.where('country', '<', 'Japan').where('region', '==', 'west').where('population', '>', 100000);
cities.where('country', '>', 'Japan').where('region', '==', 'north').where('capital', '==', true);
cities.where('country', '>', 'Japan').where('region', '==', 'north').where('population', '>', 100000);
cities.where('country', '>', 'Japan').where('region', '==', 'east').where('capital', '==', true);
cities.where('country', '>', 'Japan').where('region', '==', 'east').where('population', '>', 100000);
cities.where('country', '>', 'Japan').where('region', '==', 'west').where('capital', '==', true);
cities.where('country', '>', 'Japan').where('region', '==', 'west').where('population', '>', 100000);
`
As you can see, SQL offers a very concise and powerful way to express your query. But as they say, with great power comes great responsibility. Always be mindful of the underlying data model when using FireSQL.

Examples of supported queries:

`sql
SELECT *
FROM restaurants
`

`sql
SELECT name, price
FROM restaurants
WHERE city = 'Chicago'
`

`sql
SELECT *
FROM restaurants
WHERE category = 'Indian' AND price < 50
`

`sql
SELECT *
FROM restaurants
WHERE name LIKE 'Best%'
`

`sql
SELECT *
FROM restaurants
WHERE name LIKE 'Best%' OR city = 'Los Angeles'
`

`sql
SELECT *
FROM restaurants
WHERE city IN ( 'Raleigh', 'Nashvile', 'Denver' )
`

`sql
SELECT *
FROM restaurants
WHERE city != 'Oklahoma'
`

`sql
SELECT *
FROM restaurants
WHERE favorite = true
`

`sql
SELECT *
FROM restaurants
WHERE favorite -- Equivalent to the previous one
`

`sql
SELECT *
FROM restaurants
WHERE favorite IS NULL
`

`sql
SELECT AVG(price) AS averagePriceInChicago
FROM restaurants
WHERE city = 'Chicago'
`

`sql
SELECT city, MIN(price), AVG(price), MAX(price)
FROM restaurants
WHERE category = 'Indian'
GROUP BY city
`

`sql
SELECT *
FROM restaurants
WHERE city = 'Memphis' AND ( price < 40 OR avgRating > 8 )
ORDER BY price DESC, avgRating
`

`sql
SELECT *
FROM restaurants
WHERE price BETWEEN 25 AND 150
ORDER BY city, price
LIMIT 10
`

`sql
SELECT *
FROM restaurants
WHERE city = 'Chicago'
UNION
SELECT *
FROM restaurants
WHERE price > 200
``