# Search
# Search

Explore Qdrant's search capabilities, from basic similarity search to advanced hybrid and multimodal queries. These pages cover how to find relevant results, apply filters, combine query types, and tune search quality and latency.

## Search

[Search](/documentation/search/search/index.md) describes similarity search — finding points whose vectors are closest to a query vector in the configured vector space.

## Filtering

[Filtering](/documentation/search/filtering/index.md) lets you narrow results using payload conditions, combining database-style clauses with vector search for precise retrieval.

## Hybrid Queries

[Hybrid Queries](/documentation/search/hybrid-queries/index.md) combine multiple queries or execute them in stages, enabling fusion of dense and sparse results and complex re-ranking pipelines.

## Explore

[Explore](/documentation/search/explore/index.md) covers discovery APIs such as recommendations and random sampling for browsing and navigating collections.

## Text Search

[Text Search](/documentation/search/text-search/index.md) explains Qdrant's built-in full-text search capabilities and how to combine them with vector search.

## Search Relevance

[Search Relevance](/documentation/search/search-relevance/index.md) describes techniques to improve result ranking beyond raw vector similarity, including score boosting and re-ranking strategies.

## Low-Latency Search

[Low-Latency Search](/documentation/search/low-latency-search/index.md) covers configuration and design patterns for achieving the fastest possible query response times.