The main task of Information Technology (IT) application innovation database migration is to migrate the data structure and data from non-domestic databases to domestic databases smoothly. In view of the challenges of syntax differences and complex business logic adaptation between heterogeneous databases in the current IT application innovation database migration， a collaborative multi-knowledge Large Language Model （LLM） prompt framework for IT application innovation-oriented databases migration， CORER （Context-Objective-Rules-Examples-Response）， was proposed， the openGauss Structured Query Language （SQL） syntax rule knowledge base covering 199 SQL syntax rule types and containing 4 162 syntax rules was constructed， and the migration sample knowledge base covering 20.6% of the syntax rule types was constructed by integrating official templates and real cases. Then， the syntax rule knowledge and migration sample knowledge were injected into the LLM context based on the prompt elements， thereby matching the syntax， logic and architecture characteristics of heterogeneous databases adaptively， and guiding the LLM to complete the SQL statement refactoring accurately. Experimental results show that the accuracy of CORER in the MySQL to openGauss migration task is 93.44%， which is 1.31 percentage points higher than that of the rule-based method， and is increased by 7.02% in advanced feature scenarios such as storage procedures and triggers， verifying the comprehensive advantages of CORER in IT innovation-oriented database migration scenarios.