SurrealDB 3.0 wants to replace your five-database RAG stack with one

SurrealDB 3.0 launches with $23M in new funding and a pitch to replace multi-database RAG stacks with a single engine that handles vectors, graphs, and agent memory transactionally.
InfoQ

Redis Improves Performance of Vector Semantic Search with Multi-Threaded Query Engine

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
techtimes

How RAG and Vector Databases Improve LLMs

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...
VentureBeat

Vector database company Qdrant wants RAG to be more cost-effective

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...
dbta

Context Engineering for AI-Readiness: Enterprise RAG Architectures and Vector Databases

Today's enterprises need effective retrieval-augmented generation that extends existing data architectures without replacing current investments. As organizations face challenges in scaling RAG ...
Searchenginejournal.com

Introduction To Vector Databases And How To Use AI For SEO

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...