Modern database management systems act not only as a data storage but also implement logic of processing data flow and collecting some analytics on data. Stored procedures, functions, triggers, and views are extremely important components of DBMS encapsulating the features specified above. Microsoft SQL and PostgreSQL are two popular relational databases that have similar SQL syntax but differ in some ways. One significant challenge of migrating SQL code between these two DBMS is that MS SQL permits dynamic determination of result sets returned by stored function or procedure, which PostgreSQL does not have. Therefore, careful attention to syntax and functionality differences between the two database management systems is crucial while migrating stored procedures, functions, triggers, and views from MS SQL or Azure SQL to PostgreSQL.

One way to ensure a smooth migration is to research best practices for translating basic syntax constructions and fully understand the underlying problem. While performing a formal conversion of tokens and their combinations is a good start, it is essential to focus on the differences in syntax and functionality to avoid errors. Another critical point to consider is that local variables in PostgreSQL functions must be declared at the beginning, whereas SQL Server allows variables to be declared anywhere. Therefore, changing this habit is essential while migrating to PostgreSQL.

One significant difference between SQL syntax in MS SQL and PostgreSQL is that the trigger’s code is part of the CREATE TRIGGER statement in SQL Server or Azure SQL. Trigger’s code in PostgreSQL must be composed as a standalone function and CREATE TRIGGER statement references that function. This difference can be challenging while migrating triggers from MS SQL or Azure SQL to PostgreSQL.

To make the migration of T-SQL code less complex, one can use automation tools like the SQL Server to PostgreSQL Code Converter. This tool can help in partially automating the migration of database logic entries from SQL Server or Azure SQL to PostgreSQL. It can migrate stored procedures, functions, triggers, and views while also converting MS SQL built-in functions into PostgreSQL equivalents. Moreover, it can intelligently map predefined MS SQL types into PostgreSQL and handle reserved words and identifiers. If there is no direct connection available to SQL Server or Azure SQL, the tool can extract the source code from both the database and T-SQL script files.

SQL Server to PostgreSQL Code Converter can automate migration of basic syntax patterns and constructions, however some complicated patterns having no direct equivalent in the target SQL syntax may require manual post-processing. For example: pivot tables, recursive queries and full-text search are subject of special attention during migration of SQL code from MS SQL to PostgreSQL. Therefore, database engineers and other responsible staff must have deep expertise in programing both DBMS and carefully process every single semantic difference between SQL Server and PostgreSQL syntax patterns.

In conclusion, migrating stored procedures, functions, triggers, and views from SQL Server or Azure SQL to PostgreSQL requires careful consideration of syntax and functionality differences between the two database systems. Using best practices for translation and automation tools like the SQL Server to PostgreSQL Code Converter can simplify the process, but manual post-processing may still be necessary for complex source code fragments. Having comprehensive programming knowledge for both database systems, developers and other responsible staff can ensure smooth and easy migration using cutting edge SQL Server to PostgreSQL Code Converter.