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Vector Search Manuals
Qdrant Internals
Data Exploration
Machine Learning
RAG & GenAI
Practical Examples
Ecosystem

Learn

Vector Search Manuals
Qdrant Internals
Data Exploration
Machine Learning
RAG & GenAI
Practical Examples
Ecosystem

Vector Search Manuals

Take full control of your vector data with Qdrant. Learn how to easily store, organize, and optimize vectors for high-performance similarity search.

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Vector Search in Production

We gathered our most recommended tips and tricks to make your production deployment run smoothly.

David Myriel

April 30, 2025

Preview
Optimizing Memory for Bulk Uploads

Efficient memory management is key when handling large-scale vector data. Learn how to optimize memory consumption during bulk uploads in Qdrant and keep your deployments performant under heavy load.

Sabrina Aquino

February 13, 2025

Preview
Vector Search Resource Optimization Guide

Learn how to get the most from Qdrant's optimization features. Discover key tricks and best practices to boost vector search performance and reduce Qdrant's resource usage.

David Myriel

February 09, 2025

Qdrant Internals

Take a look under the hood of Qdrant’s high-performance vector search engine. Explore the architecture, components, and design principles the Qdrant Vector Search Engine is built on.

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Built for Vector Search

Why add-on vector search looks good — until you actually use it.

Evgeniya Sukhodolskaya & Andrey Vasnetsov

February 17, 2025

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Introducing Gridstore: Qdrant's Custom Key-Value Store

Why and how we built our own key-value store. A short technical report on our procedure and results.

Luis Cossio, Arnaud Gourlay & David Myriel

February 05, 2025

Preview
Qdrant Internals: Immutable Data Structures

Learn how immutable data structures improve vector search performance in Qdrant.

Andrey Vasnetsov

August 20, 2024

Data Exploration

Learn how you can leverage vector similarity beyond just search. Reveal hidden patterns and insights in your data, provide recommendations, and navigate data space.

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Distance-based data exploration

Explore your data under a new angle with Qdrant's tools for dimensionality reduction, clusterization, and visualization.

Andrey Vasnetsov

March 11, 2025

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Discovery needs context

Discovery Search, an innovative way to constrain the vector space in which a search is performed, relying only on vectors.

Luis Cossío

January 31, 2024

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Vector Similarity: Going Beyond Full-Text Search | Qdrant

Discover how vector similarity expands data exploration beyond full-text search. Explore diversity sampling and more for enhanced data discovery!

Luis Cossío

August 08, 2023

Machine Learning

Explore Machine Learning principles and practices which make modern semantic similarity search possible. Apply Qdrant and vector search capabilities to your ML projects.

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miniCOIL: on the Road to Usable Sparse Neural Retrieval

Introducing miniCOIL, a lightweight sparse neural retriever capable of generalization.

Evgeniya Sukhodolskaya

May 13, 2025

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Relevance Feedback in Informational Retrieval

Relerance feedback: from ancient history to LLMs. Why relevance feedback techniques are good on paper but not popular in neural search, and what we can do about it.

Evgeniya Sukhodolskaya

March 27, 2025

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Modern Sparse Neural Retrieval: From Theory to Practice

A comprehensive guide to modern sparse neural retrievers: COIL, TILDEv2, SPLADE, and more. Find out how they work and learn how to use them effectively.

Evgeniya Sukhodolskaya

October 23, 2024

RAG & GenAI

Leverage Qdrant for Retrieval-Augmented Generation (RAG) and build AI Agents

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What is Agentic RAG? Building Agents with Qdrant

Agents are a new paradigm in AI, and they are changing how we build RAG systems. Learn how to build agents with Qdrant and which framework to choose.

Kacper Łukawski

November 22, 2024

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Optimizing RAG Through an Evaluation-Based Methodology

Learn how Qdrant-powered RAG applications can be tested and iteratively improved using LLM evaluation tools like Quotient.

Atita Arora

June 12, 2024

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Semantic Cache: Accelerating AI with Lightning-Fast Data Retrieval

Semantic cache is reshaping AI applications by enabling rapid data retrieval. Discover how its implementation benefits your RAG setup.

Daniel Romero, David Myriel

May 07, 2024

Practical Examples

Building blocks and reference implementations to help you get started with Qdrant. Learn how to use Qdrant to solve real-world problems and build the next generation of AI applications.

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Optimizing OpenAI Embeddings: Enhance Efficiency with Qdrant's Binary Quantization

Explore how Qdrant's Binary Quantization can significantly improve the efficiency and performance of OpenAI's Ada-003 embeddings. Learn best practices for real-time search applications.

Nirant Kasliwal

February 21, 2024

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Food Discovery Demo

Feeling hungry? Find the perfect meal with Qdrant's multimodal semantic search.

Kacper Łukawski

September 05, 2023

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Semantic Search As You Type

To show off Qdrant's performance, we show how to do a quick search-as-you-type that will come back within a few milliseconds.

Andre Bogus

August 14, 2023

Ecosystem

Tools, libraries and integrations around Qdrant vector search engine.

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Qdrant Summer of Code 2024 - WASM based Dimension Reduction

My journey as a Qdrant Summer of Code 2024 participant working on enhancing vector visualization using WebAssembly (WASM) based dimension reduction.

Jishan Bhattacharya

August 31, 2024

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FastEmbed: Qdrant's Efficient Python Library for Embedding Generation

Learn how to accurately and efficiently create text embeddings with FastEmbed.

Nirant Kasliwal

October 18, 2023

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Google Summer of Code 2023 - Web UI for Visualization and Exploration

My journey as a Google Summer of Code 2023 student working on the "Web UI for Visualization and Exploration" project for Qdrant.

Kartik Gupta

August 28, 2023

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