Paper by Tepper et al. proposing GleanVec, a method to accelerate vector search using minimalist nonlinear dimensionality reduction. Improves efficiency for high-dimensional vector queries.

Research paper introducing LeanVec, a technique to accelerate vector search by reducing vector dimensionality while preserving search accuracy. Published as an arXiv preprint in 2023 by Mariano Tepper et al.

An OpenSearch plugin that expands its capabilities with the custom `knn_vector` data type, enabling storage of embeddings and providing methods for k-NN similarity searches, including Approximate k-NN, Script Score k-NN, and Painless extensions.

ClickHouse is a columnar OLAP database with vector indexes (ANN via AMM, brute-force), supporting SQL queries over vectors + structured data at petabyte scale. Excels in aggregations with vectors. For analytics workloads with embeddings; faster ingestion than Postgres pgvector for big data.

Vector search extension for Meilisearch engine, supporting hybrid lexical+vector search with BM25 fusion, k-NN similarity. Ideal for enterprise semantic search, RAG, and recommendations. Integrated vs standalone like Weaviate: developer-friendly with typo-tolerant full-text but lighter scale for massive vectors.

k-NN vector plugin for OpenSearch (Lucene-based), supporting hybrid lexical+vector, BM25 fusion, HNSW/IVF indexes, multimodal. For enterprise RAG, semantic search. Integrated vs standalone like Weaviate: excels in hybrid text+vector but heavier footprint.