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​.

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Production ready AI assistant framework

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

The open-source tool for building high-quality datasets and computer vision models

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

A curated list of awesome works related to high dimensional structure/vector search & database

Build LLM-powered applications in Ruby

An embedded vector database designed to run on edge devices. Lightweight and fast with HNSW indexing algorithm.

Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

Text to image search & Image Similarity Search using @typesense

VectorHub is a free, open-source learning website for people (software developers to senior ML architects) interested in adding vector retrieval to their ML stack.

Documentation used in the Search & Vector Search hands-on labs during Developer Days

Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences

All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.

JVector: the most advanced embedded vector search engine

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

cuVS - a library for vector search and clustering on the GPU

The AI-native database built for LLM applications, providing incredibly fast full-text and vector search