Qdrant, an efficient vector database, initially supported only keyword filters for semantic searches, but since version 0.10, it has enabled full-text filtering capabilities, allowing users to apply more complex constraints in conjunction with other filter types. Full-text filters can be used without an index, performing substring matches on individual query terms, or with an index, offering more options like choosing a tokenizer and setting parameters such as token length and case sensitivity. The primary advantage of using full-text indexes is improved query performance, as demonstrated in a benchmark using the H&M dataset, where indexed fields offered substantial performance gains when queried frequently.