Tags: #vector-database

An open-source vector database simplifying the storage, indexing, and querying of embeddings for AI applications.

An open-source platform for building, deploying, and orchestrating AI agents and agentic workflows with 1,000+ integrations.

An open-source knowledge engine designed to build personalized and dynamic memory for AI agents, enabling them to learn and provide relevant context.

A high-performance, cloud-native vector database designed for scalable Approximate Nearest Neighbor (ANN) search on massive unstructured data.

An all-in-one AI framework for semantic search, LLM orchestration, and language model workflows, powered by an embeddings database.

LEANN is an innovative on-device vector database enabling private, efficient, and fast Retrieval Augmented Generation (RAG) across all your personal data with significant storage savings.

A customizable AI chatbot template that ingests PDF documents, stores embeddings, and answers user queries using LLMs, orchestrated by LangChain and LangGraph.

A comprehensive, full-stack guide to Retrieval Augmented Generation (RAG) technology for large language model application development, covering theory, practice, and engineering best practices.

An open-source, cloud-native vector database enabling semantic search at scale by combining vector similarity with structured filtering and AI capabilities.

A high-performance, massive-scale vector database and search engine designed for next-generation AI applications.

A hands-on course to learn LLMs, LLMOps, and vector databases by building, training, and deploying a real-time financial advisor LLM system.

An intelligent dialogue system leveraging RAG technology to build custom Q&A systems from diverse knowledge bases.

Deep Lake is an AI data runtime and database optimized for deep learning, offering serverless multimodal data storage, scalable retrieval, and training capabilities.

An MCP plugin that provides AI coding agents like Claude Code with deep, cost-effective context from an entire codebase through semantic search.

An open-source, developer-friendly embedded retrieval library and multimodal AI lakehouse for fast, scalable vector search and data management.

A powerful open-source platform for real-time AI inference, search, and data organization across vectors, tensors, text, and structured data at any scale.

An AI-native search database that unifies relational, vector, text, JSON, and GIS data in a single engine, enabling hybrid search and in-database AI workflows.

An open-source, graph RAG-based conversational knowledge base tool built with TiDB Serverless Vector Storage, offering intelligent search and instant answers.

A cloud-native distributed vector database for efficient similarity search of embedding vectors in AI applications.

HelixDB is an open-source graph-vector database built in Rust, designed to simplify AI application development by unifying various data models into a single, low-latency platform.

Attu is a modern, AI-native management tool for Milvus vector databases, offering a comprehensive GUI for cluster management, data exploration, and AI-driven operations.

A comprehensive collection of Jupyter Notebooks and sample applications designed to help developers master Pinecone vector databases and common AI patterns through hands-on practice.

A comprehensive learning resource providing tutorials and demos to master Milvus for building advanced AI applications with unstructured data.

DeepSearcher is an open-source platform that leverages LLMs and vector databases to enable deep research, intelligent Q&A, and comprehensive reporting on private enterprise data.

A Python library for representing, transmitting, storing, and retrieving multimodal data, designed for AI applications.

A free, hands-on course to build a production-ready LLM & RAG system, including a personalized AI replica, applying LLMOps best practices.

A universal GUI and tool suite designed to simplify the management, visualization, and interaction with data stored in various vector databases like Pinecone, Chroma, Qdrant, and Weaviate, eliminating the need for direct API calls.

A declarative, transactional Python library for building multimodal AI applications with incremental data storage, transformation, indexing, and orchestration.

A collaborative, spreadsheet-like platform for building, experimenting with, and evaluating AI applications, especially those leveraging Retrieval-Augmented Generation (RAG).

PostgresML integrates machine learning and AI capabilities, including LLMs and vector search, directly into PostgreSQL, leveraging GPUs for high-performance in-database inference.

An open-source, self-hostable toolkit for testing, experimenting with, and evaluating prompts, large language models (LLMs), and vector databases.

Zvec is a lightweight, lightning-fast, in-process vector database built on Alibaba's Proxima, enabling scalable and low-latency similarity search directly within applications.

RuVector is a high-performance, self-learning vector database with integrated graph intelligence and local AI capabilities, designed for real-time, adaptive search and agentic systems.