InfoWorld

Using PostgreSQL as a vector database in RAG

As many developers have come to realize, “Just use Postgres” is generally a good strategy. If and when your needs grow, you might want to swap in a larger and more performant vector database. Until ...

Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via ...
Visual Studio Magazine

Empowering AI Applications with Vector Search in SQL Server and Azure Cosmos DB

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...
ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
VentureBeat

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

Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has ...
Business Wire

Qdrant Launches Groundbreaking Pure Vector-Based Hybrid Search, Setting Higher Standards for RAG and AI Applications

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...

VIDEO INTERVIEW: Progress Software’s John Ainsworth on agentic RAG, MCP and why bypassing business logic is "fraught with incredible risk"

You can't spell Ainsworth without AI. It's a small linguistic coincidence, but it's also a neat shorthand for the conversation I had with John Ainsworth, Executive ...