Awesome Ai Agents 2026
Section: RAG and Knowledge Bases · OSS embedding database. Fastest way to build RAG.
Entry
Appears in 8 awesome lists
An open-source embedding database for building AI applications with embeddings and semantic search.
Section: RAG and Knowledge Bases · OSS embedding database. Fastest way to build RAG.
Section: Vector Databases (RAG) · The fastest way to build Python or JavaScript LLM apps with memory!
Section: Vector search · the open source embedding database
Section: 5. Retrieval-Augmented Generation (RAG) & Knowledge · Most popular open-source embedding database.
Section: Data Storage Optimisation · Chroma is an open-source embedding database.
Section: Library
Section: Embeddings/Vector Databases · The AI-native open-source embedding database
Section: Database · An open-source embedding database for building AI applications with embeddings and semantic search.
Milvus is a cloud-native, open-source vector database built to manage embedding vectors generated by machine learning models and neural networks.
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
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.
All-in-one AI framework for semantic search, LLM orchestration and language model workflows. Embeddings database with customizable pipelines.
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).
is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete…