Hangul, the Korean alphabet created in 1443, revolutionized Korean literacy by replacing the complex Chinese characters that were accessible only to the elite, with a phonetic system consisting of 14 consonants and 10 vowels. Korean, being an agglutinative language, benefits from specialized analyzers for effective document search, as these analyzers can parse the language's complex structure of predicates and postpositions. The article discusses the performance of three open-source Korean analyzers—seunjeon, arirang, and open-korean-text—when integrated with Elasticsearch 5.5.0, evaluating their speed and memory consumption. Arirang proves to be the fastest with minimal memory variation, while seunjeon offers significant improvements in speed during the second run, and open-korean-text provides detailed part-of-speech analysis but at a slight cost to performance. The choice of analyzer is crucial, as they significantly impact indexing time and memory usage, with arirang being optimal for speed and efficiency, while seunjeon and open-korean-text offer more comprehensive linguistic analysis.