---
title: RAG with Qdrant
description: RAG, powered by Qdrant's efficient data retrieval, elevates AI's capacity to generate rich, context-aware content across text, code, and multimedia, enhancing relevance and precision on a scalable platform. Discover why Qdrant is the perfect choice for your RAG project.
features:
- id: 0
  icon:
    src: /icons/outline/speedometer-blue.svg
    alt: Speedometer
  title: Highest RPS
  description: Qdrant leads with top requests-per-second, outperforming alternative vector databases in various datasets by up to 4x.
- id: 1
  icon:
    src: /icons/outline/time-blue.svg
    alt: Time
  title: Fast Retrieval
  description: "Qdrant achieves the lowest latency, ensuring quicker response times in data retrieval: 3ms response for 1M Open AI embeddings."
- id: 2
  icon:
    src: /icons/outline/vectors-blue.svg
    alt: Vectors
  title: Multi-Vector Support
  description: Integrate the strengths of multiple vectors per document, such as title and body, to create search experiences your customers admire.
- id: 3
  icon:
    src: /icons/outline/compression-blue.svg
    alt: Compression
  title: Built-in Compression
  description: Significantly reduce memory usage, improve search performance and save up to 30x cost for high-dimensional vectors with Quantization.
sitemapExclude: true
---