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- Added: Jun 23, 2025
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Qdrant
Qdrant is a high-performance vector database and search engine for AI applications, enabling efficient similarity search and payload filtering.
Qdrant is a production-ready vector similarity search engine and vector database. It allows users to store, search, and manage vectors with associated payloads, offering advanced filtering capabilities for neural network-based matching and faceted search. Written in Rust for speed and reliability, Qdrant transforms embeddings into powerful applications for matching, recommendation, and anomaly detection.
This vector database excels in enabling semantic text search, similar image search, and extreme classification use cases. Its features like hybrid search with sparse vectors, vector quantization, and distributed deployment make it suitable for demanding AI workloads. Qdrant is ideal for developers and data scientists building next-generation AI applications requiring efficient vector management and search.
This vector database excels in enabling semantic text search, similar image search, and extreme classification use cases. Its features like hybrid search with sparse vectors, vector quantization, and distributed deployment make it suitable for demanding AI workloads. Qdrant is ideal for developers and data scientists building next-generation AI applications requiring efficient vector management and search.
- Store and search vectors with rich JSON payloads for advanced filtering.
- Perform hybrid search using both dense and sparse vectors for keyword relevance.
- Reduce RAM usage with built-in vector quantization for efficiency.
- Scale horizontally with sharding and replication for massive datasets.
- Integrate seamlessly with popular AI frameworks like LangChain and LlamaIndex.
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