Elasticsearch's Common Terms Query offers a novel approach to handling stop words in information retrieval, balancing speed and relevance by selectively ignoring high-frequency, semantically empty words during searches. Traditionally, stop words like "the" and "to" are removed from indexes to improve performance, but this can exclude important phrases composed entirely of stop words, such as "to be or not to be." The Common Terms Query addresses this by initially focusing on low-frequency, important terms and subsequently considering high-frequency words, allowing for more efficient searches without fully discarding potentially meaningful stop words. This adaptive method eliminates the need for manually curated stop word lists by automatically categorizing words based on their frequency within the specific dataset, thereby allowing for tailored optimization in various contexts. Customization options enable further refining of query behavior, enhancing both speed and precision in document retrieval while maintaining the context-dependent utility of stop words.