This documentation describes a release under development. Documentation for the latest release, 3.6.2, can be found here.

Microsoft Azure SQL

Microsoft Azure SQL can either be used as a data source or a data destination in Mitto.

Mitto connects to Azure SQL Server

Source plugin example: Query

Destination plugin examples: CSV, Salesforce, SQL

Microsoft Azure SQL as a data destination

  • Mitto automatically creates the Microsoft Azure SQL database schema if it doesn’t exist

  • Mitto automatically creates the Microsoft Azure SQL database tables if they don’t exist

  • Mitto automatically determines data types for Microsoft Azure SQL columns

  • Mitto automatically adds new columns to Microsoft Azure SQL tables based new fields in source systems

  • Mitto automatically adjusts Microsoft Azure SQL tables based on changes in source data

Microsoft Azure SQL specific setup

Below is the database url structure for connecting to an Microsoft Azure SQL database:

mssql+pyodbc://<username>:<password>@<hostname>/<database>?<parameters>

Note

Microsoft Azure SQL requires a parameter for the Microsoft Azure SQL driver. Typically this is ?driver=ODBC+Driver+17+for+SQL+Server.

Here’s an example of using an Microsoft Azure SQL database as a destination in a CSV job:

Output Data to Azure SQL Server

Note

When outputting to a Microsoft Azure SQL database, leaving the ‘Schema’ blank will create a table in the dbo schema.*

SQL

Mitto can send SQL statements to a Microsoft Azure SQL database. Use Microsoft Azure SQL syntax in these Mitto SQL jobs.