Qdrant

Qdrant is an open-source vector database written in Rust, designed for high-performance similarity search and semantic search over large collections of high-dimensional vectors. It stores vector embeddings and their associated payloads, enabling applications like recommendation systems,…

Key facts

First appeared: 2021
Category: database
Problem solved: Qdrant was created to solve the challenge of efficiently storing, indexing, and querying large volumes of high-dimensional vector embeddings to find semantically similar items. Traditional relational or NoSQL databases are not optimized for this type of similarity search, leading to inefficient and slow operations for applications requiring semantic understanding or content-based retrieval at scale.
Platforms: AWS, GCP, Kubernetes, macOS, Linux, Azure, Docker, Windows (via Docker)

Related technologies

LangChain
Kafka
TensorFlow
Python data science libraries
FastAPI
Kubernetes
LlamaIndex
PyTorch
Hugging Face Transformers
OpenAI API

Notable users

Skyscanner
NTT DOCOMO
Numerous AI/ML startups and enterprises leveraging LLMs
Genentech