Qwak

Infinity is an AI-native database built for LLM applications, offering fast hybrid search of dense vectors, sparse vectors, tensors, and full-text data.

ChromaDB (also known as Chroma or chroma-core) is an open-source vector database focused on LLM applications, emphasizing simplicity and in-memory HNSW-based dense vector search. It is suited for prototyping, metadata filtering, and offers a user-friendly interface for building and testing vector search applications, though it currently lacks hybrid and distributed features.

An advanced RAG architecture where an AI agent autonomously decides which questions to ask, which tools to use, when to retrieve information, and how to aggregate results. Represents a major trend in 2026 for more intelligent and adaptive retrieval systems.

NVIDIA's generalist embedding model achieving record 69.32 score on MTEB benchmark. Fine-tuned from Llama architecture with improved techniques for training LLMs as embedding models.

A re-ranking tool provided by Cohere, which can be integrated into LLM applications via frameworks like LangChain to improve the relevance and order of retrieved documents from search systems, including those utilizing vector databases.

A tool that allows users to run large language models locally, providing an easy way to set up and interact with various models, including integrations for generating and managing embeddings with vector databases.