Full-text filter and index are already available!
Blog post from Qdrant
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.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 1 | 336 | 71 | 38 | +26% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.