📚 从零开始的向量数据库原理与实践教程,在线阅读地址:https://easy-vecdb.datawhale.cc/
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Updated
Jun 1, 2026 - Jupyter Notebook
📚 从零开始的向量数据库原理与实践教程,在线阅读地址:https://easy-vecdb.datawhale.cc/
NeuronDB PostgreSQL extension: vector similarity search (HNSW, IVFFlat), embeddings, kNN, ML in SQL, and hybrid full-text + vector retrieval.
CLI benchmark for pgvector — measure HNSW/IVFFlat latency (p50/p95/p99), throughput, and recall@k. Single Go binary, interactive wizard, HTML report. MIT.
This project uses Python, Hugging Face (sentence-transformers), Milvus + Docker (container running Vector DB) to create a vector database, populate it with details of many people (names, ages, salaries, addresses and their introductions) and enable searching and querying on the database contents using Cosine-Similarity distances on IVF Flat index.
Comparison of IVFFlat and HNSW Algorithms
ANN search in high dimensions!
This project uses Python, Hugging Face (sentence-transformers), Milvus + Docker (container running Vector DB) to create a vector database, populate it with details of many people (names, ages, salaries, addresses and their introductions) and enable searching and querying on the database contents using Cosine-Similarity distances on IVF Flat index.
A C++ implementation of efficient Nearest Neighbor search algorithms (LSH, Random Projection Hypercube, IVFFlat, and IVFPQ) optimized for high-dimensional datasets like SIFT and MNIST.
Tune pgvector RAG retrieval latency in PostgreSQL: measure HNSW ef_search and IVFFlat probes with FastAPI, YAML profiles, telemetry, and benchmarks.
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