SQL to Mongo Mapping Chart

MySQL executable

Oracle executable

Mongo executable

mysqld

oracle

{{mongod}}

mysql

sqlplus

mongo

MySQL term

Mongo term/concept

database

database

table

collection

index

index

row

BSON document

column

BSON field

join

embedding and linking

primary key

_id field

group by

aggregation

MongoDB queries are expressed as JSON (BSON) objects.  The following chart shows examples as both SQL and in Mongo Query Language syntax. 

The query expression in MongoDB (and other things, such as index key patterns) is represented as JSON (BSON). However, the actual verb (e.g. "find") is done in one's regular programming language; thus the exact forms of these verbs vary by language.  The examples below are Javascript and can be executed from the mongo shell.

SQL Statement

Mongo Statement

CREATE TABLE USERS (a

Number, b Number)

implicit; can also be done explicitly with

db.createCollection("mycoll")

  

ALTER TABLE users ADD ...

implicit

  

  

INSERT INTO USERS VALUES(3,5)

db.users.insert({a:3,b:5})

  

  

SELECT a,b FROM users

db.users.find({}, {a:1,b:1})

SELECT * FROM users

db.users.find()

SELECT * FROM users WHERE age=33

db.users.find({age:33})

SELECT a,b FROM users WHERE age=33

db.users.find({age:33}, {a:1,b:1})

SELECT * FROM users WHERE age=33 ORDER BY name

db.users.find({age:33}).sort({name:1})

SELECT * FROM users WHERE age>33

db.users.find({age:{$gt:33}})

SELECT * FROM users WHERE age!=33

db.users.find({age:{$ne:33}})

SELECT * FROM users WHERE name LIKE

"%Joe%"

db.users.find({name:/Joe/})

SELECT * FROM users WHERE name LIKE

"Joe%"

db.users.find({name:/^Joe/})

SELECT * FROM users WHERE age>

33 AND age<=40

db.users.find({'age':{$gt:33,$lte:40}})

SELECT * FROM users ORDER BY name DESC

db.users.find().sort({name:-1})

SELECT * FROM users WHERE a=1 and b='q'

db.users.find({a:1,b:'q'})

SELECT * FROM users LIMIT 10 SKIP 20

db.users.find().limit(10).skip(20)

SELECT * FROM users WHERE a=1 or b=2

db.users.find( { $or : [ { a : 1 } , { b : 2 } ] } )

SELECT * FROM users LIMIT 1

db.users.findOne()

SELECT order_id FROM orders o, order_line_items li WHERE li.order_id=o.order_id AND li.sku=12345

db.orders.find({"items.sku":12345},{_id:1})

SELECT customer.name FROM customers,orders WHERE orders.id=

"q179" AND orders.custid=customer.id

var o = db.orders.findOne({_id:"q179"});

var name = db.customers.findOne({_id:o.custid})

  

  

SELECT DISTINCT last_name FROM users

db.users.distinct('last_name')

SELECT COUNT(*y)

FROM users

db.users.count()

SELECT COUNT(*y)

FROM users where AGE > 30

db.users.find({age: {'$gt': 30}}).count()

SELECT COUNT(AGE) from users

db.users.find({age: {'$exists': true}}).count()

  

  

CREATE INDEX myindexname ON users(name)

db.users.ensureIndex({name:1})

CREATE INDEX myindexname ON users(name,ts DESC)

db.users.ensureIndex({name:1,ts:-1})

  

  

EXPLAIN SELECT * FROM users WHERE z=3

db.users.find({z:3}).explain()

  

  

UPDATE users SET a=1 WHERE b='q'

db.users.update({b:'q'}, {$set:{a:1}}, false, true)

UPDATE users SET a=a+2 WHERE b='q'

db.users.update({b:'q'}, {$inc:{a:2}}, false, true)

  

  

DELETE FROM users WHERE z=

"abc"

db.users.remove({z:'abc'});

More examples, specifically aggregation examples, here

See Also

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