SQL to Mongo Mapping Chart

SQL to Mongo Mapping Chart

http://www.mongodb.org/display/DOCS/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