Line 2 initializes the xml_element session variable as an empty string. VALUES 1 declares an xml_element session variable. INSERT INTO marvel_xml (xml_table ) VALUES ) Here’s the way you insert relational data into an XML type column: Second, the INSERT statement disallows nested SELECT queries that include the FOR XML AUTO clause. First, the FOR XML AUTO clause doesn’t render the correct XML structure. The FOR XML AUTO doesn’t work for two reasons. Unfortunately, Microsoft didn’t make it very easy. It a lot easier to transfer relational data from a table to an XML type. There’s a lot of typing to insert XML literal values. It will fail when you use semicolons on the DECLARE or SET lines, so avoid them as shown below:
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You can run the script file with the following syntax, assuming you have a student user with student as its password working against items in the studentdb schema:ĬREATE XML SCHEMA COLLECTION MarvelXMLTable ASĪfter creating the XML Schema Collection, you can confirm whether it works correctly with the following statements. You can put a GO on line 6 in an interactive session or you can put the five lines into a T-SQL script file and call it from the sqlcmd utility. That is the value that the name identifies in the dictionary. While a dictionary is a collection of name and value pairs, you can use the name of any dictionary element as a key to return only one value from the dictionary. While the subquery on line 3 returns a multivalued SELECT-list, the assignment statement appends the value associated with the column name or alias, which acts like a key in a dictionary. WITH x AS (SELECT 'Chilly' AS cold, 'Burning up' AS hot) Multi-user collaboration using File, DBMS or (transfer via XMI, CVS/TFS or Difference Merge).WITH x AS ( SELECT 'Chilly' AS cold, 'Burning up' AS hot ) SELECT += cold FROM x Multi-user collaboration using File, DBMS or Cloud Repository (or transfer via XMI, CVS/TFS or Difference Merge).ĮR/Studio Repository and Team Server (formerly Portal/CONNECT) for web based publishing collaboration and model management, with Business Glossary as standard. IDEF1X, UML DDL, Information Engineering & ERD Model/database comparison and synchronizationĬonceptual, Logical & Physical + MDA Transform of Logical to Physical
Supported data models (conceptual, logical, physical) Standalone with Data, UML, and process modelingĪccess, Greenplum, Apache Hive, HP Neoview, IBM Db2, Informix, Ingres, Interbase, MySQL, Netezza, NonStop SQL, Oracle, PostgreSQL, Red Brick Warehouse, SAP business Suite, SAP Hana, SAP Adaptive Server Enterprise, SAP IQ, SAP SQL Anywhere, MS SQL Server, TeradataĪccess, IBM Db2, Informix, MySQL, MariaDB, PostgreSQL, MS SQL Server, SQLite, OracleĢ005 (before this date known as CaseStudio)
MS SQL Server, MySQL, PostgreSQL, Oracle, IBM Db2 MySQL, MS SQL Server, PostgreSQL, Oracle, IBM Db2 MySQL, MS SQL Server, PostgreSQL, Oracle, SQLite MS SQL Server, Oracle, MySQL, PostgreSQL, IBM Db2Īccess, MS SQL Server, Oracle, MySQL, PostgreSQL, IBM Db2 Windows, Linux (Wine), macOS (via CrossOver)ĭata modeling is supported as part of a complete modeling platform.Īccess, Snowflake, Microsoft Azure IBM Db2, Informix, Hitachi HiRDB, Firebird, Interbase, MySQL, MS SQL Server, Netezza, Oracle, PostgreSQL, Sybase, Teradata, Visual Foxpro and others via ODBC/ANSI SQLĪccess, IBM Db2, Informix, MySQL, MS SQL Server, Netezza, Oracle, PostgreSQL, Sybase, and others via ODBC/ANSI SQL IBM Db2, Firebird, InterBase, Informix, Ingres, Access, MS SQL Server, MySQL, SQLite, Oracle, PostgreSQL, Sybase Windows, Linux and FreeBSD (both through Wine) MS SQL Server, MySQL, Oracle, Firebird, InterBase, SQL Anywhere, NexusDB, MariaDB Standalone or bundled into a larger toolkit This article is a comparison of data modeling tools which are notable, including standalone, conventional data modeling tools and modeling tools supporting data modeling as part of a larger modeling environment. Comparison of notable data modeling tools
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