SQL to MongoDB Mapping Chart

October 8, 2014 · by · in MongoDB

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 the MySQL/Oracle executables and the corresponding MongoDB executables.

MySQL/Oracle MongoDB
Database Server mysqld/oracle mongod
Database Client mysql/sqlplus mongo

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:
  • {
  • :”509a8fb2f3f4948bd2f983a0″),
  • : “abc123”,
  • : 55,
  • : ‘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.

  1. db.users.insert( {

user_id: “abc123”,

age: 55,

status: “A”

} )

However, you can also explicitly create a collection:

  1. 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.

  1. 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.

  1. db.users.update(

{ },

{ $unset: { join_date: “” } },

{ multi: true }

)
CREATE INDEX idx_user_id_asc

ON users(user_id)
  1. db.users.ensureIndex( { user_id: 1 } )
CREATE INDEX

idx_user_id_asc_age_desc

ON users(user_id, age DESC)
  1. db.users.ensureIndex( { user_id: 1, age: -1 } )
DROP TABLE users
  1. 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”)
  1. 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
  1. db.users.find()
SELECT id,

user_id,

status

FROM users
  1. db.users.find(

{ },

{ user_id: 1, status: 1 }

)
SELECT user_id, status

FROM users
  1. db.users.find(

{ },

{ user_id: 1, status: 1, _id: 0 }

)
SELECT *

FROM users

WHERE status = “A”
  1. db.users.find(

{ status: “A” }

)
SELECT user_id, status

FROM users

WHERE status = “A”
  1. db.users.find(

{ status: “A” },

{ user_id: 1, status: 1, _id: 0 }

)
SELECT *

FROM users

WHERE status != “A”
  1. db.users.find(

{ status: { $ne: “A” } }

)
SELECT *

FROM users

WHERE status = “A”

AND age = 50
  1. db.users.find(

{ status: “A”,

age: 50 }

)
SELECT *

FROM users

WHERE status = “A”

OR age = 50
  1. db.users.find(

{ $or: [ { status: “A” } ,

{ age: 50 } ] }

)
SELECT *

FROM users

WHERE age > 25
  1. db.users.find(

{ age: { $gt: 25 } }

)
SELECT *

FROM users

WHERE age < 25
  1. db.users.find(

{ age: { $lt: 25 } }

)
SELECT *

FROM users

WHERE age > 25

AND   age <= 50
  1. db.users.find(

{ age: { $gt: 25, $lte: 50 } }

)
SELECT *

FROM users

WHERE user_id like “%bc%”
  1. db.users.find( { user_id: /bc/ } )
SELECT *

FROM users

WHERE user_id like “bc%”
  1. db.users.find( { user_id: /^bc/ } )
SELECT *

FROM users

WHERE status = “A”

ORDER BY user_id ASC
  1. db.users.find( { status: “A” } ).sort( { user_id: 1 } )
SELECT *

FROM users

WHERE status = “A”

ORDER BY user_id DESC
  1. db.users.find( { status: “A” } ).sort( { user_id: -1 } )
SELECT COUNT(*)

FROM users
  1. db.users.count()

or

  1. db.users.find().count()
SELECT COUNT(user_id)

FROM users
  1. db.users.count( { user_id: { $exists: true } } )

or

  1. db.users.find( { user_id: { $exists: true } } ).count()
SELECT COUNT(*)

FROM users

WHERE age > 30
  1. db.users.count( { age: { $gt: 30 } } )

or

  1. db.users.find( { age: { $gt: 30 } } ).count()
SELECT DISTINCT(status)

FROM users
  1. db.users.distinct( “status” )
SELECT *

FROM users

LIMIT 1
  1. db.users.findOne()

or

  1. db.users.find().limit(1)
SELECT *

FROM users

LIMIT 5

SKIP 10
  1. db.users.find().limit(5).skip(10)
EXPLAIN SELECT *

FROM users

WHERE status = “A”
  1. 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
  1. db.users.update(

{ age: { $gt: 25 } },

{ $set: { status: “C” } },

{ multi: true }

)
UPDATE users

SET age = age + 3

WHERE status = “A”
  1. 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”
  1. db.users.remove( { status: “D” } )
DELETE FROM users
  1. db.users.remove({})

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

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.

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