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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 $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 the SQL to Aggregation Mapping Chart.
SELECT INTO NEW_TABLE

$out

See the SQL to Aggregation Mapping Chart.
MERGE INTO TABLE

$merge (Available starting in MongoDB 4.2)

See the SQL to Aggregation Mapping Chart.
UNION ALL $unionWith (Available starting in MongoDB 4.4)
transactions

transactions

Tip

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 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 people.

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

    copy 
    {
  _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 people
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, updateMany() operations can add fields to existing documents using the $set operator.

db.people.updateMany(
    { },
    { $set: { join_date: new Date() } }
)

ALTER TABLE people
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, updateMany() operations can remove fields from documents using the $unset operator.

db.people.updateMany(
    { },
    { $unset: { "join_date": "" } }
)

CREATE INDEX idx_user_id_asc
ON people(user_id)

db.people.createIndex( { user_id: 1 } )

CREATE INDEX
       idx_user_id_asc_age_desc
ON 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:

See also

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().

See also

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,
       status
FROM people

db.people.find(
    { },
    { user_id: 1, status: 1 }
)

SELECT user_id, status
FROM people

db.people.find(
    { },
    { user_id: 1, status: 1, _id: 0 }
)

SELECT *
FROM people
WHERE status = "A"

db.people.find(
    { status: "A" }
)

SELECT user_id, status
FROM people
WHERE status = "A"

db.people.find(
    { status: "A" },
    { user_id: 1, status: 1, _id: 0 }
)

SELECT *
FROM people
WHERE status != "A"

db.people.find(
    { status: { $ne: "A" } }
)

SELECT *
FROM people
WHERE status = "A"
AND age = 50

db.people.find(
    { status: "A",
      age: 50 }
)

SELECT *
FROM people
WHERE status = "A"
OR age = 50

db.people.find(
    { $or: [ { status: "A" } , { age: 50 } ] }
)

SELECT *
FROM people
WHERE age > 25

db.people.find(
    { age: { $gt: 25 } }
)

SELECT *
FROM people
WHERE age < 25

db.people.find(
   { age: { $lt: 25 } }
)

SELECT *
FROM people
WHERE age > 25
AND   age <= 50

db.people.find(
   { age: { $gt: 25, $lte: 50 } }
)

SELECT *
FROM people
WHERE user_id like "%bc%"

db.people.find( { user_id: /bc/ } )

-or-

db.people.find( { user_id: { $regex: /bc/ } } )

SELECT *
FROM people
WHERE user_id like "bc%"

db.people.find( { user_id: /^bc/ } )

-or-

db.people.find( { user_id: { $regex: /^bc/ } } )

SELECT *
FROM people
WHERE status = "A"
ORDER BY user_id ASC

db.people.find( { status: "A" } ).sort( { user_id: 1 } )

SELECT *
FROM people
WHERE 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 people
WHERE 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 people
LIMIT 1

db.people.findOne()

or

db.people.find().limit(1)

SELECT *
FROM people
LIMIT 5
SKIP 10

db.people.find().limit(5).skip(10)

EXPLAIN SELECT *
FROM people
WHERE status = "A"

db.people.find( { status: "A" } ).explain()

For more information on the methods and operators used, see

See also

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 people
SET status = "C"
WHERE age > 25

db.people.updateMany(
   { age: { $gt: 25 } },
   { $set: { status: "C" } }
)

UPDATE people
SET age = age + 3
WHERE status = "A"

db.people.updateMany(
   { status: "A" } ,
   { $inc: { age: 3 } }
)

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

See also

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 people
WHERE status = "D"

db.people.deleteMany( { status: "D" } )

DELETE FROM people

db.people.deleteMany({})

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

See also

Further Reading

If you are considering migrating your SQL application to MongoDB, download the MongoDB Application Modernization Guide.

The download includes the following resources:

  • Presentation on the methodology of data modeling with MongoDB
  • White paper covering best practices and considerations for migrating to MongoDB from an RDBMS data model
  • Reference MongoDB schema with its RDBMS equivalent
  • Application Modernization scorecard

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