Awesome Ai Agents 2026
Section: RAG and Knowledge Bases · Cloud-native vector DB. Billion-scale.
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Appears in 14 awesome lists
Milvus is a cloud-native, open-source vector database built to manage embedding vectors generated by machine learning models and neural networks.
Section: RAG and Knowledge Bases · Cloud-native vector DB. Billion-scale.
Section: Vector Databases · open-source vector database for scalable similarity search.
Section: Databases · Vector database for scalable similarity search and AI applications.
Section: Vector Databases (RAG) · Milvus is an open-source vector database built to power embedding similarity search and AI applications.
Section: Databases Implemented in Go · Milvus is a vector database for embedding management, analytics and search.
Section: Go中实现的数据库 · star:42514 Milvus是一个矢量数据库,用于嵌入管理、分析和搜索。
Section: Vector search · Vector database for scalable similarity search and AI applications.
Section: Data Management · An open source embedding vector similarity search engine powered by Faiss, NMSLIB and Annoy.
Section: 5. Retrieval-Augmented Generation (RAG) & Knowledge · Scalable cloud-native vector database.
Section: vector-database · 一个云原生向量数据库,为下一代人工智能应用提供存储
Section: Data Storage Optimisation · Milvus is a cloud-native, open-source vector database built to manage embedding vectors generated by machine learning models and neural networks.
Section: Standalone Service
Section: 数据库 · 向量数据库
Section: Other · Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Mem0 is an intelligent memory layer for Large Language Models that enhances personalized AI experiences by retaining and utilizing contextual information across various applications. github | website | docs | discord | twitter | github profile | linkedin
TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No noisy neighbors. No infrastructure ceiling.
AI-native database built for LLM applications with incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text. Powers RAGFlow's document engine. Apache 2.0 licensed.
Vector Search Engine and Database for the next generation of AI applications. Also available in the cloud
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Features 350+ connectors with always-in-sync data from SharePoint, Google Drive, S3, Kafka, PostgreSQL and more. BSL 1.1 license (becomes Apache 2.0 after 4 years).
An open-source embedding database for building AI applications with embeddings and semantic search.