Query processing and optimization play a crucial role in enhancing the efficiency of database systems by reducing query execution time and improving overall system performance. In this paper, we have integrated various approaches to optimize query execution time and minimize costs by eliminating poorly constructed SQL statements. The optimization process involves considering potential query plans based on lineage, aiming to identify the most efficient way to execute a specific query. Our approach incorporates several key components, including a scanner and parser, intermediate query representation, and a query optimizer. By evaluating the order of all clauses, multiple query execution plans can be generated. The query optimizer then selects the most efficient plan, influencing the ultimate result of the query. This study underscores the significance of employing diverse query optimization techniques and sheds light on their effectiveness. Ultimately, the insights gained from this research can assist both database administrators and developers in making well-informed decisions when selecting the most suitable query optimization technique for their specific database system.