Vector Search
Showing 32 of 32 projects
Ready-to-deploy Docker templates for building real-time RAG, AI pipelines, and enterprise search applications with live data sync.
A high-performance, cloud-native vector database built for scalable approximate nearest neighbor (ANN) search.
A library for efficient similarity search and clustering of dense vectors, scaling to billions of vectors on a single server.
An open-source query engine for AI analytics that builds self-reasoning agents across live data sources without ETL.
A high-performance vector database and search engine written in Rust, designed for AI applications with filtering and payload support.
Turso is an in-process SQL database written in Rust, compatible with SQLite, offering async I/O, vector search, and multi-language support.
An open-source, cloud-native vector database that combines semantic search with structured filtering for AI applications.
An all-in-one AI framework for semantic search, LLM orchestration, and language model workflows built around an embeddings database.
An open-source, fast, and easy-to-use database designed for full-text and hybrid search, serving as a drop-in replacement for Elasticsearch.
A modern indexing and search library for Go supporting text, numeric, geo-spatial, and vector data.
An open-source embedded retrieval library for multimodal AI, offering fast vector search, SQL, and full-text search.
An open-source enterprise data warehouse built in Rust for AI agents, analytics, vector search, and full-text search.
A comprehensive collection of PostgreSQL, Greenplum, and AI-related technical articles, tutorials, and learning resources.
A semantic cache library for LLM queries that reduces API costs by 10x and boosts response speed by 100x.
An open-source feature store for managing and serving machine learning features for training and online inference.
An AI-native database built for LLM applications, offering incredibly fast hybrid search across vectors, tensors, and full-text.
A fast, single-file similarity search and clustering engine for vectors and arbitrary objects with multi-language bindings.
Embedded property graph database optimized for speed with built-in vector search, full-text search, and Cypher query language.
A Ruby library for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Ruby gem for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A portable mixed-precision math library with 2,000+ SIMD kernels for 15+ numeric types across x86, Arm, RISC-V, and WebAssembly.
An embedded graph database optimized for query speed and scalability on complex analytical workloads.
An embeddable vector database for Go with a Chroma-like interface, enabling RAG and semantic search without external dependencies.
Embeddable, in-memory, document-oriented database with a high-level Query builder interface, designed for fast search with complex queries.
A universal HTAP engine providing ACID transactions and real-time analytics across diverse databases.
A modular multi-modal transactional database for AI and semantic search, replacing MongoDB, Neo4J, and Elastic with a single ACID solution.
A document-oriented in-memory database optimized for fast real-time data searches, inspired by Erlang Mnesia.
A Go library implementing word embedding models (Word2Vec, GloVe, LexVec) from scratch with CLI and SDK.
AI-powered search and chat interface for your Kindle highlights using embeddings and GPT.
A local-first desktop app for searching documents, images, and audio across devices using natural language.
Adds structured AI outputs, vectorization, and tool calling to Ash Framework applications using ReqLLM.
A .NET library providing an in-memory data structure with efficient indexing and querying, including range, spatial, vector, and fuzzy string matching.
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