Files
landing_page/qdrant-landing/content/headless/main/why-qdrant.md
T
1a40961d62 fix: linkchecker include filter port mismatch (#2242)
* initial commit; fixed anchor links on internal docs pages

* add back in absolute paths for links in code comments

* fix: update linkchecker include filter to match server port 1314

PR #1629 changed the Hugo server to port 1314 but forgot to update
the --include filter, which still matched port 1313. This caused all
links to be excluded, making the checker a no-op (0 checked, 82277 excluded).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Fix url rewrite regex so images are not impacted

* Fix links from non-documentation pages

* Fix broken links

* more broken links

* more broken links

* broken link

* Add srcset width descriptor to .lycheeignore

* Ignore URLs that contain a % character

* Anchor regex so it matches the entire URL

---------

Co-authored-by: kanungle <neil.kanungo@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
2026-03-30 17:21:32 +02:00

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---
title: Build for Production-Grade AI Search
subtitle: Engineered for real-time retrieval with the speed, accuracy, and scale that modern AI demands.
pill: WHY QDRANT?
featureCards:
- id: metadata-filters
title: Expansive Metadata Filters
description: "Store metadata in JSON and use advanced filters, such as <code>nested</code>, <code>text</code>, <code>geo</code>, <code>has_vector</code>, and more."
image:
src: /img/home/metadata-filters.png
alt: Metadata filters code illustration
link:
text: Learn About Metadata Filters
url: /documentation/manage-data/payload/
size: large
- id: hybrid-search
title: Native Hybrid Search (Dense + Sparse)
description: Blend keyword and vector search in one query – use dense or sparse vectors. Supports BM25, SPLADE++, and miniCOIL.
image:
src: /img/home/native-hybrid-search.png
alt: Native hybrid search illustration
link:
text: Explore Hybrid Search
url: /documentation/search/hybrid-queries/
size: large
- id: multivector
title: Built-in Multivector
description: Set new standards for relevance; make the retrieval layer more expressive, flexible, and multimodal with multiple vectors per object.
image:
src: /img/home/multivector.png
alt: Multivector illustration
link:
text: See Documentation
url: /documentation/tutorials-search-engineering/using-multivector-representations/
size: small
- id: one-stage-filtering
title: Efficient, One-Stage Filtering
description: Filters are applied during HNSW traversal — no pre- or post-filtering. High recall with low latency, even under complex conditions.
image:
src: /img/home/one-stage-filtering.png
alt: One-stage filtering illustration
link:
text: See Documentation
url: /articles/filterable-hnsw/
size: small
- id: reranking
title: Full-Spectrum Reranking
description: Infuse business logic with score boosting, achieve token-level precision with late interaction models (e.g. ColBERT), diversify results with Maximum Marginal Relevance (MMR)
image:
src: /img/home/reranking.png
alt: Reranking illustration
link:
text: See Documentation
url: /documentation/tutorials-search-engineering/reranking-hybrid-search/
size: small
sitemapExclude: true
---