Each data warehouse requires loading properly processed transactional data. The process that performs this task is known as extract-transform-load (ETL). The efficiency of its implementation affects how quickly the user will have the access to the current analytical data. The paper presents the results of research efficiency of ETL performance of its stage with the use of Azure Synapse (AS) and Azure Data Factory (ADF). The research included selection, sorting and aggregating data, joining tables, and loading data into target tables. To evaluate the efficiency of these operations, the criterion of their execution time has been used. The obtained results indicate that the ADF tool provides a much higher time efficiency of loading transactional data into the data warehouse comparing to AS.