SQL to MongoDB Mapping Chart

http://docs.mongodb.org/manual/reference/sql-comparison/

In addition to the charts that follow, you might want to consider the Frequently Asked Questions section for a selection of common questions about MongoDB.

Terminology and Concepts

The following table presents the various SQL terminology and concepts and the corresponding MongoDB terminology and concepts.

SQL Terms/Concepts	MongoDB Terms/Concepts
database	database
table	collection
row	document or BSON document
column	field
index	index
table joins	embedded documents and linking
primary key Specify any unique column or column combination as primary key.	primary key In MongoDB, the primary key is automatically set to the _id field.
aggregation (e.g. group by)	aggregation pipeline See the SQL to Aggregation Mapping Chart.

Executables

The following table presents some database executables and the corresponding MongoDB executables. This table is not meant to be exhaustive.

	MongoDB	MySQL	Oracle	Informix	DB2
Database Server	mongod	mysqld	oracle	IDS	DB2 Server
Database Client	mongo	mysql	sqlplus	DB-Access	DB2 Client

Examples

The following table presents the various SQL statements and the corresponding MongoDB statements. The examples in the table assume the following conditions:

• The SQL examples assume a table named users.

• The MongoDB examples assume a collection named users that contain documents of the following prototype:

  {
    _id: ObjectId("509a8fb2f3f4948bd2f983a0"),
    user_id: "abc123",
    age: 55,
    status: 'A'
  }
  

Create and Alter

The following table presents the various SQL statements related to table-level actions and the corresponding MongoDB statements.

SQL Schema Statements	MongoDB Schema Statements
CREATE TABLE users ( id MEDIUMINT NOT NULL AUTO_INCREMENT, user_id Varchar(30), age Number, status char(1), PRIMARY KEY (id) )	Implicitly created on first insert() operation. The primary key _id is automatically added if _id field is not specified. db.users.insert( { user_id: "abc123", age: 55, status: "A" } ) However, you can also explicitly create a collection: db.createCollection("users")
ALTER TABLE users ADD join_date DATETIME	Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can add fields to existing documents using the $set operator. db.users.update( { }, { $set: { join_date: new Date() } }, { multi: true } )
ALTER TABLE users DROP COLUMN join_date	Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can remove fields from documents using the $unset operator. db.users.update( { }, { $unset: { join_date: "" } }, { multi: true } )
CREATE INDEX idx_user_id_asc ON users(user_id)	db.users.ensureIndex( { user_id: 1 } )
CREATE INDEX idx_user_id_asc_age_desc ON users(user_id, age DESC)	db.users.ensureIndex( { user_id: 1, age: -1 } )
DROP TABLE users	db.users.drop()

For more information, see db.collection.insert(), db.createCollection(), db.collection.update(), $set, $unset, db.collection.ensureIndex(), indexes, db.collection.drop(), and Data Modeling Concepts.

Insert

The following table presents the various SQL statements related to inserting records into tables and the corresponding MongoDB statements.

SQL INSERT Statements	MongoDB insert() Statements
INSERT INTO users(user_id, age, status) VALUES ("bcd001", 45, "A")	db.users.insert( { user_id: "bcd001", age: 45, status: "A" } )

For more information, see db.collection.insert().

Select

The following table presents the various SQL statements related to reading records from tables and the corresponding MongoDB statements.

SQL SELECT Statements	MongoDB find() Statements
SELECT * FROM users	db.users.find()
SELECT id, user_id, status FROM users	db.users.find( { }, { user_id: 1, status: 1 } )
SELECT user_id, status FROM users	db.users.find( { }, { user_id: 1, status: 1, _id: 0 } )
SELECT * FROM users WHERE status = "A"	db.users.find( { status: "A" } )
SELECT user_id, status FROM users WHERE status = "A"	db.users.find( { status: "A" }, { user_id: 1, status: 1, _id: 0 } )
SELECT * FROM users WHERE status != "A"	db.users.find( { status: { $ne: "A" } } )
SELECT * FROM users WHERE status = "A" AND age = 50	db.users.find( { status: "A", age: 50 } )
SELECT * FROM users WHERE status = "A" OR age = 50	db.users.find( { $or: [ { status: "A" } , { age: 50 } ] } )
SELECT * FROM users WHERE age > 25	db.users.find( { age: { $gt: 25 } } )
SELECT * FROM users WHERE age < 25	db.users.find( { age: { $lt: 25 } } )
SELECT * FROM users WHERE age > 25 AND age <= 50	db.users.find( { age: { $gt: 25, $lte: 50 } } )
SELECT * FROM users WHERE user_id like "%bc%"	db.users.find( { user_id: /bc/ } )
SELECT * FROM users WHERE user_id like "bc%"	db.users.find( { user_id: /^bc/ } )
SELECT * FROM users WHERE status = "A" ORDER BY user_id ASC	db.users.find( { status: "A" } ).sort( { user_id: 1 } )
SELECT * FROM users WHERE status = "A" ORDER BY user_id DESC	db.users.find( { status: "A" } ).sort( { user_id: -1 } )
SELECT COUNT(*) FROM users	db.users.count() or db.users.find().count()
SELECT COUNT(user_id) FROM users	db.users.count( { user_id: { $exists: true } } ) or db.users.find( { user_id: { $exists: true } } ).count()
SELECT COUNT(*) FROM users WHERE age > 30	db.users.count( { age: { $gt: 30 } } ) or db.users.find( { age: { $gt: 30 } } ).count()
SELECT DISTINCT(status) FROM users	db.users.distinct( "status" )
SELECT * FROM users LIMIT 1	db.users.findOne() or db.users.find().limit(1)
SELECT * FROM users LIMIT 5 SKIP 10	db.users.find().limit(5).skip(10)
EXPLAIN SELECT * FROM users WHERE status = "A"	db.users.find( { status: "A" } ).explain()

For more information, see db.collection.find(), db.collection.distinct(), db.collection.findOne(), $ne $and, $or, $gt, $lt, $exists, $lte, $regex, limit(), skip(), explain(), sort(), and count().

Update Records

The following table presents the various SQL statements related to updating existing records in tables and the corresponding MongoDB statements.

SQL Update Statements	MongoDB update() Statements
UPDATE users SET status = "C" WHERE age > 25	db.users.update( { age: { $gt: 25 } }, { $set: { status: "C" } }, { multi: true } )
UPDATE users SET age = age + 3 WHERE status = "A"	db.users.update( { status: "A" } , { $inc: { age: 3 } }, { multi: true } )

For more information, see db.collection.update(), $set, $inc, and $gt.

Delete Records

The following table presents the various SQL statements related to deleting records from tables and the corresponding MongoDB statements.

SQL Delete Statements	MongoDB remove() Statements
DELETE FROM users WHERE status = "D"	db.users.remove( { status: "D" } )
DELETE FROM users	db.users.remove({})

For more information, see db.collection.remove().