Qdrant Internals: Immutable Data Structures
Learn how immutable data structures improve vector search performance in Qdrant.
Andrey Vasnetsov
·August 20, 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.
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
Binary Quantization - Vector Search, 40x Faster
Binary Quantization is a newly introduced mechanism of reducing the memory footprint and increasing performance
Nirant Kasliwal
·September 18, 2023
Qdrant under the hood: io_uring
Slow disk decelerating your Qdrant deployment? Get on top of IO overhead with this one trick!
Andre Bogus
·June 21, 2023
Product Quantization in Vector Search | Qdrant
Discover product quantization in vector search technology. Learn how it optimizes storage and accelerates search processes for high-dimensional data.
Kacper Łukawski
·May 30, 2023
Scalar Quantization: Background, Practices & More | Qdrant
Discover the efficiency of scalar quantization for optimized data storage and enhanced performance. Learn about its data compression benefits and efficiency improvements.
Kacper Łukawski
·March 27, 2023
Minimal RAM you need to serve a million vectors
How to properly measure RAM usage and optimize Qdrant for memory consumption.
Andrei Vasnetsov
·December 07, 2022
Filtrable HNSW
How to make ANN search with custom filtering? Search in selected subsets without loosing the results.
Andrei Vasnetsov
·November 24, 2019