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Comparación sentencias MongoDB con SQL
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 | embedded documents and linking |
|
primary key Specify any unique column or column combination as primary key. |
In MongoDB, the primary key is automatically set to the _idfield. |
| 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 users.
-
The MongoDB examples assume a collection named users 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 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().
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
|
db.users.update(
{ age: { $gt: 25 } },
{ $set: { status: "C" } },
{ multi: true }
)
|
UPDATE users
SET age = age + 3
WHERE status = "A"
|
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"
|
db.users.remove( { status: "D" } )
|
DELETE FROM users
|
db.users.remove({})
|
For more information, see db.collection.remove().
Fuente completa en: https://docs.mongodb.com/v3.2/reference/sql-comparison/
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