A cloud-native vector database, storage for next generation AI applications
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Updated
Oct 14, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
mlpack: a fast, header-only C++ machine learning library
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Statistical Machine Intelligence & Learning Engine
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Open-source vector similarity search for Postgres
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
📝Awesome and classical image retrieval papers
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
Represent, send, store and search multimodal data
FAst Lookups of Cosine and Other Nearest Neighbors (based on fast locality-sensitive hashing)
Open source audio fingerprinting in .NET. An efficient algorithm for acoustic fingerprinting written purely in C#.
Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
A Python nearest neighbor descent for approximate nearest neighbors
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
Collections of vector search related libraries, service and research papers
A Java library implementing practical nearest neighbour search algorithm for multidimensional vectors that operates in sublinear time. It implements Locality-sensitive Hashing (LSH) and multi index hashing for hamming space.
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