InfoWorld

Using PostgreSQL as a vector database in RAG

PostgreSQL with the pgvector extension allows tables to be used as storage for vectors, each of which is saved as a row. It also allows any number of metadata columns to be added. In an enterprise ...
VentureBeat

Vectorize debuts agentic RAG platform for real time enterprise data

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now While vector databases are now increasingly ...
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 ...
InfoWorld

Teradata adds Enterprise Vector Store to augment RAG

Teradata’s partnership with Nvidia will allow developers to fine-tune NeMo Retriever microservices with custom models to build document ingestion and RAG applications. Teradata is adding vector ...

Agents need vector search more than RAG ever did

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the retrieval problem up. Here's what production deployments from GlassDollar ...

RAG vs Long Context for LLMs : When Each Approach Works Best

Choosing RAG or long context depends on dataset size, with RAG suited to dynamic knowledge bases and long context best for ...
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 ...