Seamless Data Migration between Database Schemas with DAMI-Framework: An Empirical Study on Developer Experience

Many businesses depend on legacy systems, which often use outdated technology that complicates maintenance and updates. Therefore, software modernization is essential, particularly data migration between different database schemas. Established methodologies, like model transformation and ETL tools, facilitate this migration. However, these methodologies require deep knowledge of database languages and both the source and target schemas. This necessity renders data migration an error-prone and cognitively demanding task. Our objective is to alleviate developers’ workloads during schema evolution by proposing DAMI-Framework. This framework incorporates a domain-specific language (DSL) and a parser to facilitate data migration between database schemas. DAMI-DSL simplifies schema mapping, while the parser automates SQL script generation. To evaluate DAMI-Framework, we conducted an empirical evaluation with 21 developers to assess their experiences using our DSL versus traditional SQL. The study allows us to measure their perceptions of the DSL properties and user experience. The participants praised DAMI-DSL for its readability and ease of use. The findings indicate that our framework has positive impact in data migration efforts compared to SQL scripts, by reducing the lines of code and characters required for the migration by 18.3% and 35.6%, respectively.