Free Lesson
The many shades of text search in vector retrieval
Part of Building Production AI Systems
45 min
Oct 2, 2025 12:00 PM
Virtual (Zoom)
In this video
What you'll learn
Mismatched Expectations from traditional to vector search
How expectations from a traditional, keyword based search engine don't always translate
Dense vs Sparse Retrieval
What are the differences between dense and sparse neural retrieval with text?
How QDrant thinks about text retrieval
QDrant's core "opinions" about text retrieval (text, vector, filters), and that leads to their implementation
Why this topic matters
Approaching text in vector search is not easy! Text search comes with expectations from traditional search engines that when carried into vector search, lead to unexpected results and dissatisfaction.
We’ll discuss the different types of text search from filtering, rule, and BM25-based ranking, to sparse neural and dense vector retrieval how/why each approach is (or isn’t) included in QDrant.
You'll learn from
Evgeniya Sukhodolskaya
DevRel QDrant
Doug Turnbull
Search consultant
Previously at
