#python #cloud #cloud_native #computer_vision #deep_learning #docker #framework #image_search #jina #machine_learning #microservice #neural_search #nlp #pytorch #search #semantic_search #tensorflow #transformers #video_search #zmq

https://github.com/jina-ai/jina

#rust #search_engine #machine_learning #algorithm #neural_network #high_performance #artificial_intelligence #simd #data_structures #image_search #recommender_system #approximate_nearest_neighbor_search #similarity_search #k_nearest_neighbors #hnsw #vector_search

https://github.com/hora-search/hora

#rust #approximate_nearest_neighbor_search #embeddings_similarity #hnsw #image_search #knn_algorithm #machine_learning #matching #mlops #nearest_neighbor_search #neural_network #neural_search #recommender_system #search #search_engine #search_engines #similarity_search #vector_database #vector_search #vector_search_engine

https://github.com/qdrant/qdrant

#go #approximate_nearest_neighbor_search #generative_search #grpc #hnsw #hybrid_search #image_search #information_retrieval #mlops #nearest_neighbor_search #neural_search #recommender_system #search_engine #semantic_search #semantic_search_engine #similarity_search #vector_database #vector_search #vector_search_engine #vectors #weaviate

Weaviate is a powerful, open-source vector database that uses machine learning to make your data searchable. It's fast, scalable, and flexible, allowing you to vectorize your data at import or upload your own vectors. Weaviate supports various modules for integrating with popular AI services like OpenAI, Cohere, and Hugging Face. It's designed for production use with features like scaling, replication, and security. You can use Weaviate for tasks beyond search, such as recommendations, summarization, and integration with neural search frameworks. It offers APIs in GraphQL, REST, and gRPC and has client libraries for several programming languages. This makes it easy to build applications like chatbots, recommendation systems, and image search tools quickly and efficiently. Joining the Weaviate community provides access to tutorials, demos, blogs, and forums to help you get started and stay updated.

https://github.com/weaviate/weaviate

#go #anns #cloud_native #distributed #embedding_database #embedding_similarity #embedding_store #faiss #golang #hnsw #image_search #llm #nearest_neighbor_search #tensor_database #vector_database #vector_search #vector_similarity #vector_store

Milvus is an open-source vector database designed for embedding similarity search and AI applications. It makes unstructured data search more accessible and provides a consistent user experience across different deployment environments. Key features include millisecond search on trillion vector datasets, simplified unstructured data management, reliable and always-on operations, high scalability, and hybrid search capabilities. Milvus is cloud-native, supports multiple SDKs, and has a strong community with extensive documentation and support channels like Discord and mailing lists. Using Milvus benefits users by enabling fast and efficient vector searches, simplifying data management, and ensuring reliability and scalability in their applications.

https://github.com/milvus-io/milvus