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SQL to MongoDB Mapping Chart

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

table

row

document or BSON document

column

index

table joins

$lookup, embedded documents

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 SQL to Aggregation Mapping Chart.

SELECT INTO NEW_TABLE

MERGE INTO TABLE

UNION ALL

transactions

transactions

For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases instead of multi-document transactions. That is, for many scenarios, modeling your data appropriately will minimize the need for multi-document transactions.

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

mysqld

oracle

IDS

DB2 Server

Database Client

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 people.

  • The MongoDB examples assume a collection named people 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 people (    id MEDIUMINT NOT NULL        AUTO_INCREMENT,    user_id Varchar(30),    age Number,    status char(1),    PRIMARY KEY (id))

Implicitly created on first insertOne() or insertMany() operation. The primary key _id is automatically added if _id field is not specified.

db.people.insertOne( {    user_id: "abc123",    age: 55,    status: "A" } )

However, you can also explicitly create a collection:

db.createCollection("people")
ALTER TABLE peopleADD 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, updateMany() operations can add fields to existing documents using the $set operator.

db.people.updateMany(    { },    { $set: { join_date: new Date() } })
ALTER TABLE peopleDROP 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, updateMany() operations can remove fields from documents using the $unset operator.

db.people.updateMany(    { },    { $unset: { "join_date": "" } })
CREATE INDEX idx_user_id_ascON people(user_id)
db.people.createIndex( { user_id: 1 } )
CREATE INDEX       idx_user_id_asc_age_descON people(user_id, age DESC)
db.people.createIndex( { user_id: 1, age: -1 } )
DROP TABLE people
db.people.drop()

For more information on the methods and operators used, see:

Insert

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

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

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

Select

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

Note

The find() method always includes the _id field in the returned documents unless specifically excluded through projection. Some of the SQL queries below may include an _id field to reflect this, even if the field is not included in the corresponding find() query.

SQL SELECT Statements
MongoDB find() Statements
SELECT *FROM people
db.people.find()
SELECT id,       user_id,       statusFROM people
db.people.find(    { },    { user_id: 1, status: 1 })
SELECT user_id, statusFROM people
db.people.find(    { },    { user_id: 1, status: 1, _id: 0 })
SELECT *FROM peopleWHERE status = "A"
db.people.find(    { status: "A" })
SELECT user_id, statusFROM peopleWHERE status = "A"
db.people.find(    { status: "A" },    { user_id: 1, status: 1, _id: 0 })
SELECT *FROM peopleWHERE status != "A"
db.people.find(    { status: { $ne: "A" } })
SELECT *FROM peopleWHERE status = "A"AND age = 50
db.people.find(    { status: "A",      age: 50 })
SELECT *FROM peopleWHERE status = "A"OR age = 50
db.people.find(    { $or: [ { status: "A" } , { age: 50 } ] })
SELECT *FROM peopleWHERE age > 25
db.people.find(    { age: { $gt: 25 } })
SELECT *FROM peopleWHERE age < 25
db.people.find(   { age: { $lt: 25 } })
SELECT *FROM peopleWHERE age > 25AND   age <= 50
db.people.find(   { age: { $gt: 25, $lte: 50 } })
SELECT *FROM peopleWHERE user_id like "%bc%"
db.people.find( { user_id: /bc/ } )

-or-

db.people.find( { user_id: { $regex: /bc/ } } )
SELECT *FROM peopleWHERE user_id like "bc%"
db.people.find( { user_id: /^bc/ } )

-or-

db.people.find( { user_id: { $regex: /^bc/ } } )
SELECT *FROM peopleWHERE status = "A"ORDER BY user_id ASC
db.people.find( { status: "A" } ).sort( { user_id: 1 } )
SELECT *FROM peopleWHERE status = "A"ORDER BY user_id DESC
db.people.find( { status: "A" } ).sort( { user_id: -1 } )
SELECT COUNT(*)FROM people
db.people.count()

or

db.people.find().count()
SELECT COUNT(user_id)FROM people
db.people.count( { user_id: { $exists: true } } )

or

db.people.find( { user_id: { $exists: true } } ).count()
SELECT COUNT(*)FROM peopleWHERE age > 30
db.people.count( { age: { $gt: 30 } } )

or

db.people.find( { age: { $gt: 30 } } ).count()
SELECT DISTINCT(status)FROM people
db.people.aggregate( [ { $group : { _id : "$status" } } ] )

or, for distinct value sets that do not exceed the BSON size limit

db.people.distinct( "status" )
SELECT *FROM peopleLIMIT 1
db.people.findOne()

or

db.people.find().limit(1)
SELECT *FROM peopleLIMIT 5SKIP 10
db.people.find().limit(5).skip(10)
EXPLAIN SELECT *FROM peopleWHERE status = "A"
db.people.find( { status: "A" } ).explain()

For more information on the methods and operators used, see

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 updateMany() Statements
UPDATE peopleSET status = "C"WHERE age > 25
db.people.updateMany(   { age: { $gt: 25 } },   { $set: { status: "C" } })
UPDATE peopleSET age = age + 3WHERE status = "A"
db.people.updateMany(   { status: "A" } ,   { $inc: { age: 3 } })

For more information on the method and operators used in the examples, see:

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 deleteMany() Statements
DELETE FROM peopleWHERE status = "D"
db.people.deleteMany( { status: "D" } )
DELETE FROM people
db.people.deleteMany({})

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

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