Optimizing search query performance in Full-Text Search (FTS) is crucial for meeting the latency and throughput requirements of business-critical applications. One recommendation is to search as few fields as possible by indexing multiple document fields against a common field, reducing the complexity of composite queries. For fuzzy match queries, specifying a prefix length can minimize the number of tokens searched, improving performance by focusing fuzziness on text portions more prone to errors. In situations where text relevancy isn't important, skipping the default scoring process can enhance query efficiency. For deeper page searches, keyset pagination can reduce memory usage by focusing on sort values rather than offsets. Additionally, avoiding duplicate search clauses in composite queries prevents redundant processing and ensures optimal query formation. These strategies are applicable across various hardware configurations and cluster topologies, enhancing the effectiveness of FTS implementations.