How Dataverse SQL differs from Transact-SQL
This article describes the differences between Dataverse SQL and Transact-SQL. Dataverse SQL is a subset of Transact-SQL.
In a SQL database, each column, local variable, expression, and parameter has a related data type. A data type is an attribute that specifies the type of data that the object can hold: integer data, character data, monetary data, date and time data, binary strings, and so on.
More information: Data types (Transact-SQL)
- nvarchar(max) # multi-line text
A SQL statement is an atomic unit of work and either completely succeeds or completely fails. A SQL statement is a set of instruction that consists of identifiers, parameters, variables, names, data types, and SQL reserved words that compiles successfully.
More information: Transact-SQL statements
- SELECT column
- SELECT expression
- SELECT STAR
- SELECT distinct
- SELECT TOP
- SELECT SET Variable
- All JOIN types
- All WHERE conditions
- All nested queries (SELECT, FROM, WHERE)
- PIVOT and UNPIVOT
- GROUP BY/Having
- IF THEN ELSE
- DECLARE variable
Learn about the categories of built-in functions you can use with Dataverse environments through the SQL endpoint.
More information: What are the SQL database functions?
The following system functions perform operations on and return information about values, objects, and settings in the Dataverse environment.
More information: System Functions (Transact-SQL)
The following scalar functions return information about the environment and environment objects.
More information: Metadata Functions (Transact-SQL)
The Dataverse SQL endpoint supports the following language elements.
More information: Language Elements (Transact-SQL)
Language elements General
Use these statements to query data from the Dataverse SQL endpoint.
More information: Queries
Retrieves rows from a Dataverse environment and enables the selection of one or many rows or columns from one or many tables.
SELECT GROUP BY
FROM plus JOIN, APPLY, PIVOT
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