Statistics for topic vector-database
RepositoryStats tracks 595,858 Github repositories, of these 196 are tagged with the vector-database topic. The most common primary language for repositories using this topic is Python (63). Other languages include: TypeScript (32), Jupyter Notebook (24), Go (16), Rust (13), C++ (11)
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A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
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, a...
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A cloud-native vector database, storage for next generation AI applications
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
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, a...
Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications
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, a...
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A cloud-native vector database, storage for next generation AI applications
NNV(No-Named.V) is a vector database that supports Multi-Vector Search, high-performance HNSW, FLAT and quantization, and enables fast searches through sophisticated internal data shard design.
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
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。
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, a...
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
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, a...
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
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。
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
Private & local AI personal knowledge management app for high entropy people.
Private & local AI personal knowledge management app for high entropy people.
In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Semantic Search on Wikipedia with Upstash Vector
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector