Qdrant
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud.
Qdrant is built in Rust, distributed under the Apache License 2.0, 30.3k GitHub stars from 100 contributors, latest release v1.17.1.
When to use Qdrant
Qdrant is listed here as a Database project. The directory calls out High-performance vector search, Massive-scale storage, AI-ready infrastructure as capabilities associated with it.
Other recorded traits for Qdrant include Cloud availability, Open-source.
Besides Database, this page also files Qdrant under Development, AI, DevOps.
Qdrant compared with
Records in this directory name Pinecone, Vectara, FAISS as products people compare with Qdrant. That list is editorial metadata, not a claim that Qdrant replaces each of them.
Open-source projects that mention Qdrant are collected on a separate alternatives page.
What the Qdrant stats reflect
GitHub currently shows 30.3k GitHub stars, about 100 contributors, 2.2k forks, 506 open issues, latest tracked release v1.17.1. Star and activity counts here are a snapshot used as a proxy for community adoption, not a quality score.
Stats refreshed
- Language
- Rust
- Latest Release
- v1.17.1
- License
- Apache License 2.0
Our Newsletter
Get new Database tools right in your inbox
Get short emails with useful database projects, releases, and repos worth watching.
Key features of Qdrant
- High-performance vector search
- Massive-scale storage
- AI-ready infrastructure
- Cloud availability
- Open-source
See open-source alternatives to Qdrant
Qdrant resources
Qdrant on GitHub
Frequently asked questions
What is Qdrant?
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud. This directory highlights High-performance vector search, Massive-scale storage, AI-ready infrastructure.
Is Qdrant free to use?
Qdrant is published as open source under the Apache License 2.0. The directory lists High-performance vector search, Massive-scale storage, AI-ready infrastructure among its recorded capabilities.
What language is Qdrant written in, and what is the latest release?
Qdrant is written primarily in Rust. The latest release tracked on this page is v1.17.1.
How widely is Qdrant used on GitHub?
Qdrant has about 30.3k GitHub stars across about 100 contributors. It also has about 2.2k forks. Those counts are a snapshot of community attention, not a ranking of quality.
What do people compare Qdrant with?
This directory records Pinecone, Vectara, FAISS as comparison points for Qdrant. A longer list of open-source projects that mention Qdrant is at https://www.open-source-tools.com/alternatives/qdrant.
Related tools
Chroma
Chroma is an open-source search and retrieval database designed specifically for AI applications. It enables efficient vector storage, similarity search, and large-scale retrieval necessary for modern machine learning and LLM-powered projects.
Weaviate
Weaviate is an open-source vector database designed to store and manage both objects and vectors, enabling combined vector search with structured filtering. It offers fault tolerance, scalability, and is built as a cloud-native, developer-friendly solution for semantic search and AI-powered applications.
Sonic
Sonic is a fast, lightweight, and schema-less search backend. It serves as an alternative to Elasticsearch, designed to run on minimal resources, making it ideal for applications with limited memory availability. Sonic offers an efficient search and indexing mechanism at high speed while being easy to integrate.
Postgresml
Postgres enhanced with GPU acceleration for efficient machine learning and AI applications.
Vitess
Vitess is a powerful database clustering system designed for horizontal scaling of MySQL, enabling distributed systems to manage massive databases effectively.
Pgvector
Open-source vector similarity search extension for PostgreSQL, enabling efficient and accurate vector-based data retrieval.