Modern database management systems not only act as data storage but also process data flow and collect analytics. Stored procedures, functions, triggers, and views are essential components of DBMS that encapsulate these features. Although Microsoft SQL or Azure SQL and PostgreSQL have similar SQL syntax, they differ in several ways, making it challenging to migrate SQL code between them.
One significant challenge of migrating SQL code between MS SQL and PostgreSQL is that MS SQL allows dynamic determination of result sets returned by stored functions or procedures, while PostgreSQL does not. This fact proves that migrating database logic units such as stored procedures, functions, triggers and views requires careful attention to syntax and functionality differences between the two database management systems.
Research of best practices for translating basic syntax constructions can be a good start for smooth and safe migration of database logic from SQL Server or Azure SQL to PostgreSQL. However, performing a formal conversion of tokens and their combinations must be combined with focusing on the differences in syntax and functionality to avoid semantic errors in migration result. For example, while migrating to PostgreSQL, it is necessary to declare local variables at the beginning, whereas SQL Server allows variables to be declared anywhere.
One of the most significant challenges during migration of source code from MS SQL to PostgreSQL is that the trigger’s code is part of the CREATE TRIGGER statement in SQL Server or Azure SQL but in PostgreSQL it must be composed as a standalone function, and CREATE TRIGGER statement references that function. For example, MS SQL trigger:
CREATE TRIGGER UpdateTranscriptionistID
AFTER INSERT OR UPDATE ON Reports
FOR EACH ROW
BEGIN
UPDATE Study
SET AssignedTranscriptionist = NEW.CreatedBy
WHERE StudyUID = NEW.StudyUID AND ReportCount = 0
END;
must be migrate to PostgreSQL as follows:
CREATE FUNCTION UpdateTranscriptionistID_proc() RETURNS trigger AS $$
BEGIN
UPDATE Study
SET AssignedTranscriptionist = NEW.CreatedBy
WHERE StudyUID = NEW.StudyUID AND ReportCount = 0;
END;
$$ LANGUAGE plpgsql;
CREATE TRIGGER UpdateAssignedTranscriptionistID
AFTER INSERT OR UPDATE ON Reports
FOR EACH ROW EXECUTE PROCEDURE UpdateAssignedTranscriptionistID_proc();
To avoid spending a lot of time and resources on manual migration of stored procedures, functions, triggers and views, it is reasonable to use helper tools like the SQL Server to PostgreSQL Code Converter to make the overall process less complicated. The migration of all database logic entries from SQL Server or Azure SQL to PostgreSQL can be partially automated by this program since it has the capability to migrate non-complicated syntax patterns of SQL involved in stored procedures, functions, triggers, and views and convert MS SQL built-in functions to their PostgreSQL equivalents. In addition, it can also map predefined MS SQL types to PostgreSQL and handle reserved words and identifiers intelligently. If there is no direct connection to SQL Server or Azure SQL, the tool can extract the source code from both the database and T-SQL script files.
However, even using SQL Server to PostgreSQL Code Converter some complicated patterns that have no direct equivalent in the target SQL syntax may still require manual post-processing. Examples of such patterns include pivot tables, recursive queries, and full-text search, which require special attention during the migration of SQL code from MS SQL to PostgreSQL. Therefore, database developers and other responsible staff must have extensive skills in programming both database management systems and carefully process every single semantic difference between SQL Server and PostgreSQL syntax patterns.
To summarize, the process of migrating stored procedures, functions, triggers, and views from SQL Server or Azure SQL to PostgreSQL demands careful attention to the differences in syntax and functionality between the two database systems. The use of best practices for translation and automation tools like the SQL Server to PostgreSQL Code Converter can make the process more straightforward, but manual post-processing may be required for intricate source code fragments. It is crucial for developers and other responsible staff to have extensive programming knowledge for both database systems to guarantee a seamless and effortless migration utilizing advanced technologies.
