An Introduction to Vector Databases
Discover what a vector database is, its core functionalities, and real-world applications.
Sabrina Aquino
·October 09, 2024
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.
What is Vector Quantization?
In this article, we'll teach you about compression methods like Scalar, Product, and Binary Quantization. Learn how to choose the best method for your specific application.
Sabrina Aquino
·September 25, 2024
A Complete Guide to Filtering in Vector Search
Learn everything about filtering in Qdrant. Discover key tricks and best practices to boost semantic search performance and reduce Qdrant's resource usage.
Sabrina Aquino, David Myriel
·September 10, 2024
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.
Qdrant Internals: Immutable Data Structures
Learn how immutable data structures improve vector search performance in Qdrant.
Andrey Vasnetsov
·August 20, 2024
Vector Search as a dedicated service
Why vector search requires a dedicated service.
Andrey Vasnetsov
·November 30, 2023
Google Summer of Code 2023 - Polygon Geo Filter for Qdrant Vector Database
A Summary of my work and experience at Qdrant's Gsoc '23.
Zein Wen
·October 12, 2023
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.
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
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
Finding errors in datasets with Similarity Search
Improving quality of text-and-images datasets on the online furniture marketplace example.
George Panchuk
·July 18, 2022
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.
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
Qdrant Summer of Code 2024 - ONNX Cross Encoders in Python
A summary of my work and experience at Qdrant Summer of Code 2024.
Huong (Celine) Hoang
·October 14, 2024
Any* Embedding Model Can Become a Late Interaction Model... If You Give It a Chance!
We recently discovered that embedding models can become late interaction models & can perform surprisingly well in some scenarios. See what we learned here.
Kacper Łukawski
·August 14, 2024
RAG & GenAI
Leverage Qdrant for Retrieval-Augmented Generation (RAG) and build AI Agents
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
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
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.
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
Food Discovery Demo
Feeling hungry? Find the perfect meal with Qdrant's multimodal semantic search.
Kacper Łukawski
·September 05, 2023
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.
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
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
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