Vector Databases293 / 181 projects

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

LlamaIndex is the leading document agent and OCR platform

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

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

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

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​.

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

A lightweight, lightning-fast, in-process vector database

A vector index built on TurboQuant, written in Rust with Python bindings

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.

Refine high-quality datasets and visual AI models

🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.

The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.

Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.

Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

MariaDB server is a community developed fork of MySQL server. Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry.

Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.

The AI search platform

Postgres with GPUs for ML/AI apps.

A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.

HelixDB is an OLTP graph-vector database built in Rust on Object Storage.

Superduper: End-to-end framework for building custom AI applications and agents.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines

CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.

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

ACID Document Database

OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.

The Best GUI for Milvus

Jupyter Notebooks to help you get hands-on with Pinecone vector databases

pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai

All-in-one platform for search, recommendations, RAG, and analytics offered via API

Open-source inference server and production cluster for all the models your agent needs.

🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

Distributed vector search for AI-native applications

A new SOTA for RAG — an original retrieval architecture and an open-source knowledge base for humans and agents.

The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.

Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database.

The Virtual Feature Store. Turn your existing data infrastructure into a feature store.

SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.

AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.

SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐

Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.

Unified multimodal backend for AI data apps

A simple, fast and versatile Datalog database

The open document intelligence platform for builders and hackers - DMS for the agentic world

Python SDK for Milvus Vector Database

Infinispan is an open source data grid platform and highly scalable NoSQL cloud data store.

Python client for Qdrant vector search engine

Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/

Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀

Benchmark for vector databases.

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.

Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.

A @ClickHouse fork that supports high-performance vector search and full-text search.

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.

Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone

Ship RAG based LLM web apps in seconds.

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs

RAG-Fusion: multi-query generation + Reciprocal Rank Fusion for better retrieval-augmented generation. Includes evaluation harness with NFCorpus/BEIR.

This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!

Similarities: a toolkit for similarity calculation and semantic search. 相似度计算、匹配搜索工具包，支持亿级数据文搜文、文搜图、图搜图，python3开发，开箱即用。

RAG Time: A 5-week Learning Journey to Mastering RAG

PostgreSQL vector database extension for building AI applications

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

Epsilla is a high performance Vector Database Management System

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

An LLM-powered advanced RAG pipeline built from scratch

Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.

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

Single-file memory layer for AI agents, sub mili-second RAG on Apple Silicon. Metal Optimized On-Device. No Server. No API. One File. Pure Swift

NucliaDB, The AI Search database for RAG

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

A Python vector database you just need - no more, no less.

A NodeJS RAG framework to easily work with LLMs and embeddings

C# .NET NOSQL ( key value, object store embedded TextSearch SemanticSearch Vector layer ) ACID multi-paradigm database management system.

Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.

The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data.

NextPlaid, ColGREP: Multi-vector search, from database to coding agents.

A dead-simple API to build LLM-powered apps

GraphRAG-rs is a high-performance, state-of-the-art Rust implementation of GraphRAG (Graph-based Retrieval Augmented Generation) that builds knowledge graphs from documents and enables natural language querying with configurable entity extraction and local LLM integration

JavaScript/Typescript SDK for Qdrant Vector Database

KgCLUE: 大规模中文开源知识图谱问答

Official Python SDK for the Pinecone vector database

Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint

A tiny embedding database in pure Rust.

RAG (Retrieval-augmented generation) ChatBot that provides answers based on contextual information extracted from a collection of Markdown files.

Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.

Super performant RAG pipelines for AI apps. Summarization, Retrieve/Rerank and Code Interpreters in one simple API.

Quickly and easily build AI website or application by using embeddings!

Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.

Optimized local inference for LLMs with HuggingFace-like APIs for quantization, vision/language models, multimodal agents, speech, vector DB, and RAG.

An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.

Vector search engine inside Milvus, integrating FAISS, HNSW, DiskANN.

In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.

Program that lets you ask questions about your documents, audio, and video files.

Framework for benchmarking vector search engines

Fast, SQL powered, in-process vector search for any language with an SQLite driver

Lightweight Nearest Neighbors with Flexible Backends

Powerful unsupervised domain adaptation method for dense retrieval. Requires only unlabeled corpus and yields massive improvement: "GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval" https://arxiv.org/abs/2112.07577

Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents.

Neural Search

Weaviate vector database – examples

A Modern GUI Interface for Vector Database Management(Supports MCP integration)

EntityDB is an in-browser vector database wrapping indexedDB and Transformers.js over WebAssembly

Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.

Admin UI for Chroma embedding database built with Next.js

Radient turns many data types (not just text) into vectors for similarity search, RAG, regression analysis, and more.

RAG-QA-Generator 是一个用于检索增强生成（RAG）系统的自动化知识库构建与管理工具。该工具通过读取文档数据，利用大规模语言模型生成高质量的问答对（QA对），并将这些数据插入数据库中，实现RAG系统知识库的自动化构建和管理。

The official TypeScript/Node client for the Pinecone vector database

High-Performance Engine for Multi-Vector Search

🦉⚡️Serverless, distributed vector database as an API

Client Side Vector Database

Client Side Vector Database

Comprehensive Vector Data Tooling. The universal interface for all vector database, datasets and RAG platforms. Easily export, import, backup, re-embed (using any model) or access your vector data from any vector databases or repository.

Web-optimized vector database (written in Rust).

OramaCore is the complete runtime you need for your projects, answer engines, copilots, and search. It includes a fully-fledged full-text search engine, vector database, LLM interface, and many more utilities.

A modern desktop application for exploring, managing, and analyzing vector databases

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

Local-first, zero-key semantic code search for large and custom codebases — hybrid vector + keyword retrieval with symbol-aware chunking. Usable as a CLI, Python library, REST API, or web UI.

Cut LLM costs by up to 80% and unlock sub-millisecond responses with intelligent semantic caching.A drop-in, provider-agnostic LLM proxy written in Go with sub-millisecond response

Suite of tools containing an in-memory vector datastore and AI proxy

An official lightweight library for the RaBitQ algorithm and its applications in vector search.

High performance embedded vector database

The Kubernetes operator for K8ssandra

Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.

⚡ A fast embedded library for approximate nearest neighbor search

Python client for Antarys vector database, optimized for large-scale vector operations with built-in caching, parallel processing, and dimension validation.

In-memory vector index for Go

Strwythura: construct an entity-resolved knowledge graph from structured data sources and unstructured content sources, implementing an ontology pipeline, plus context engineering for optimizing AI application outcomes within a specific domain. This produces a Streamlit app, with MLOps instrumentation.

⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.

Swift Vector Database. On-device, local vector database for building the next-generation of user experiences

Open-source protocol suite standardizing LLM, Vector, Graph, and Embedding infrastructure across LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, and MCP. 3,330+ conformance tests. One protocol. Any framework. Any provider.

A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.

AlayaLite – A Fast, Flexible Vector Database for Everyone.

A simple, easy-to-hack Vector Database

MSVBASE is a system that efficiently supports complex queries of both approximate similarity search and relational operators. It integrates high-dimensional vector indices into PostgreSQL, a relational database to facilitate complex approximate similarity queries.

Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST API and MCP support for AI clients.

Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.

Self-hostable RAG platform - document ingestion, embedding, and vector search behind a simple REST API

Official Weaviate TypeScript Client

OasisDB: A minimal and lightweight vector database

A resource-efficient C++ vector index engine built for low-RAM production workloads

Selfhost modern LLM stacks. Run the whole fleet from your terminal

A decentralized vector database for building vector search applications

Skardi is an agent data plane that gives AI agents data autonomy.

GenAI/RAG Optimizer and Toolkit for experimentation using Oracle Database AI Vector Search and NL2SQL

Samples about using vector in SQL Server and Azure SQL

Milvus management GUI

Vectorless, Reasoning-Based Retrieval-Augmented Generation (RAG)

Graph-vector database that queried 1 billion edges for $2.50. Rust, OpenCypher, vector search, 14 graph algorithms. 74M nodes / 1B edges on a single machine.

Official Java client for Qdrant

A comprehensive toolkit for deploying production-ready Generative AI infrastructure on Amazon EKS. Includes pre-configured components for: 🚀 AI Gateway (LiteLLM) 🤖 LLM Serving (vLLM, SGLang, Ollama) 📊 Vector Databases, 🔍 Embedding Models (TEI) 📈 Observability (Langfuse, Phoenix) etc. Fast-track your GenAI deployment with Kubernetes

From data to vector database effortlessly

Browse the top 10,000 packages on PyPI with the help of vector embeddings

VQLite - Simple and Lightweight Vector Search Engine based on Google ScaNN

World's fastest and most compact embedded vector database: exact by default, multimodal, local-first, and GPU-accelerated

🐊 Snappy's unique approach unifies vision-language late interaction with structured OCR for region-level knowledge retrieval. Like the project? Drop a star! ⭐

High-quality search for AI-native applications.

chm to markdown and vectorDB

A simple vector database: Text encoding, semantic search, document storage

Website for the Weaviate vector database

Secure, locally-run Retrieval-Augmented Generation system for document-based question-answering, utilizing Llama 3, Mistral, and Gemini models with a user-friendly Streamlit interface.

Template for AI chatbots & document management using Retrieval-Augmented Generation with vector search and FastAPI.

Batteries Included is a Kubernetes based software platform for database, ai, web, monitoring, and more.

Production-ready KV-backed HNSW implementation in Rust using LMDB

The explainable, local-first memory engine for AI agents. One ~9 MB binary fuses vector + graph + columnar under VelesQL; why() returns the evidence path behind every recall. No cloud, no glue code — runs on server, browser, mobile and desktop.

Framework for benchmarking fully-managed vector databases

SNKV — a lightweight key-value store focused on simplicity, security and performance file based database , written using sqlite's b-tree directly. Now supports vector HNSW , Join the discussion: https://discord.gg/EUb4Y5qE

Object storage for the AI age

Deploy production-ready AI services in minutes. One YAML file for agents, RAG pipelines, and MCP servers — run anywhere. Inspired by docker-compose.

Reliable and Efficient Semantic Prompt Caching with vCache

RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).

ChronoMind: Redefining Vector Intelligence Through Time.

Official repository of the kANNolo library.

Three examples of recommendation system pipelines with NVIDIA Merlin and Redis

The repo has been moved to https://github.com/VectorDB-NTU/RaBitQ-Library. [SIGMOD 2025] Practical and Asymptotically Optimal Quantization of High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search

Sentence Transformers API: An OpenAI compatible embedding API server

An Amazon S3 service implementation based on Netty.

High level library for batched embeddings generation, blazingly-fast web-based RAG and quantized indexes processing ⚡

Pinecone.io Golang Client

Semantic search in Unity!

Cloud-native vector similarity search and storage with efficient, serverless scale-out

Build Recommender System with PyTorch + Redis + Elasticsearch + Feast + Triton + Flask. Vector Recall, DeepFM Ranking and Web Application.

Sorted Data Structure Server - Treds is a Data Structure Server which returns data in sorted order and is the fastest prefix search server. It also persists data on disk.

Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)

hnswlib-wasm attempts to create a browser friendly version of hnswlib

Fast search engine on object storage, with full text search, vectors, and SQL, natively on Parquet.