Qdrant is a blazing fast vector database and search engine optimized for embedding similarity queries. Filter results on rich payload data types. Scales distributed. Integrates with LangChain, LlamaIndex, OpenAI & more. Code in Rust.
Qdrant is an ultra performant open-source vector database and search engine purpose-built for lightning fast similarity queries on embedding vectors. It enables building customized semantic search and recommendations applications powered by neural networks.
⚡️ Optimized for speed with efficient algorithms and SIMD acceleration
🔎 Filter vectors on string, numeric, geospatial payload data types
🚀 Horizontally scalable architecture, handles high throughput
🛠️ Pure Rust foundation enhances reliability and security
🔗 Integrations with LangChain, LlamaIndex, OpenAI, Microsoft Semantic Kernel
Whether you want to build an intuitive search engine, shoppable feed, content discovery platform or media duplicate detector, Qdrant provides the vector storage and retrieval foundation.
It delivers versatile tooling to apply constraints and business logic on similarities using its rich query interface. Check out the interactive demos and benchmark comparisons to see blazing fast performance first-hand!
- 👨💻 It provides an easy-to-use API to build neural search applications quickly. Less time fussing with infrastructure means faster development.
- 🚀 It offers state-of-the-art speed for vector similarity search to power real-time recommendations and matching. Fast response times keep users engaged.
- ⚡️ It scales horizontally to handle growing data volumes cost efficiently. No need to overprovision hardware upfront. Add nodes as needed.
- 🧮 It enables filtering and business logic on top of vector search results. More flexibility to tailor the search experience.
- 🔒 It ensures high availability and data persistence through features like write-ahead logging. Applications remain operational 24/7.
- 👷🏽♀️ Builders: Andrey Vasnetsov, Tim Visée, Ivan Pleshkov, Egor Ivkov, Roman Titov, Kacper Łukawski
- 👩🏽💼 Builders on LinkedIn: https://www.linkedin.com/in/andrey-vasnetsov-75268897, https://www.linkedin.com/in/timvisee/, https://www.linkedin.com/in/ivan-pleshkov/, https://www.linkedin.com/in/egor-ivkov/, https://www.linkedin.com/in/ffuugoo/, https://www.linkedin.com/in/kacperlukawski/
- 👩🏽🏭 Builders on Twitter: generall931, likecaffeinated, egor_ivkov, LukawskiKacper
- 👩🏽💻 Contributors: 72
- 💫 GitHub Stars: 14.7k
- 🍴 Forks: 839
- 👁️ Watch: 105
- 🪪 License: Apache-2.0
- 🔗 Links: Below 👇🏽
- GitHub Repository: https://github.com/qdrant/qdrant
- Official Website: https://qdrant.tech/
- Twitter account: https://twitter.com/qdrant_engine
- Profile in The AI Engineer: https://github.com/theaiengineer/awesome-opensource-ai-engineering/blob/main/libraries/qdrant.md
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