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SQL to MongoDB Mapping Chart
http://docs.mongodb.org/manual/reference/sql-comparison/
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 | embedded documents and linking |
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. |
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 usersADD 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 usersDROP 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_ascON users(user_id) | db.users.ensureIndex( { user_id: 1 } ) |
CREATE INDEX idx_user_id_asc_age_descON users(user_id, age DESC) | db.users.ensureIndex( { 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.ensureIndex(), 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.
| SQL SELECT Statements | MongoDB find() Statements |
|---|---|
SELECT *FROM users | db.users.find() |
SELECT id, user_id, statusFROM users | db.users.find( { }, { user_id: 1, status: 1 }) |
SELECT user_id, statusFROM users | db.users.find( { }, { user_id: 1, status: 1, _id: 0 }) |
SELECT *FROM usersWHERE status = "A" | db.users.find( { status: "A" }) |
SELECT user_id, statusFROM usersWHERE status = "A" | db.users.find( { status: "A" }, { user_id: 1, status: 1, _id: 0 }) |
SELECT *FROM usersWHERE status != "A" | db.users.find( { status: { $ne: "A" } }) |
SELECT *FROM usersWHERE status = "A"AND age = 50 | db.users.find( { status: "A", age: 50 }) |
SELECT *FROM usersWHERE status = "A"OR age = 50 | db.users.find( { $or: [ { status: "A" } , { age: 50 } ] }) |
SELECT *FROM usersWHERE age > 25 | db.users.find( { age: { $gt: 25 } }) |
SELECT *FROM usersWHERE age < 25 | db.users.find( { age: { $lt: 25 } }) |
SELECT *FROM usersWHERE age > 25AND age <= 50 | db.users.find( { age: { $gt: 25, $lte: 50 } }) |
SELECT *FROM usersWHERE user_id like "%bc%" | db.users.find( { user_id: /bc/ } ) |
SELECT *FROM usersWHERE user_id like "bc%" | db.users.find( { user_id: /^bc/ } ) |
SELECT *FROM usersWHERE status = "A"ORDER BY user_id ASC | db.users.find( { status: "A" } ).sort( { user_id: 1 } ) |
SELECT *FROM usersWHERE 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 usersWHERE 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 usersLIMIT 1 | db.users.findOne()or db.users.find().limit(1) |
SELECT *FROM usersLIMIT 5SKIP 10 | db.users.find().limit(5).skip(10) |
EXPLAIN SELECT *FROM usersWHERE 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 usersSET status = "C"WHERE age > 25 | db.users.update( { age: { $gt: 25 } }, { $set: { status: "C" } }, { multi: true }) |
UPDATE usersSET age = age + 3WHERE 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 usersWHERE status = "D" | db.users.remove( { status: "D" } ) |
DELETE FROM users | db.users.remove({}) |
For more information, see db.collection.remove().