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SQL to MongoDB Mapping Chart¶
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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. |
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
people.The MongoDB examples assume a collection named
peoplethat 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 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, 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, 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, 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,
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.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, 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 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, see db.collection.updateMany(),
$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 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().