MongoDB vs SQL
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.createIndex( { user_id: 1 } )
|
CREATE INDEX
idx_user_id_asc_age_desc
ON users(user_id, age DESC)
| db.users.createIndex( { 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.createIndex(), 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.
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 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().
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 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().
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().
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