In this paper, a comprehensive performance analysis of duplicate data detection techniques for relational databases has been performed. The research focuses on traditional SQL based and modern bloom filter techniques to find and eliminate records which already exist in the database while performing bulk insertion operation (i.e. bulk insertion involved in the loading phase of the Extract, Transform, and Load (ETL) process and data synchronization in multisite database synchronization). The comprehensive performance analysis was performed on several data sizes using SQL, bloom filter, and parallel bloom filter. The results show that the parallel bloom filter is highly suitable for duplicate detection in the database.