Vector databases don't get as much love as their flashier counterparts, large language models (LLMs). But the startups building them are still crucial to the current AI revolution, and investors are ...

Vector databases store, index, filter, and search embeddings so applications can retrieve items by similarity at operational ...

Elastic N.V. launched its Elasticsearch Vector Database, a serverless AI search product with 32x memory reduction targeting RAG and AI agent ...

This expansion is fueled by the rapid adoption of AI, LLMs, and multimodal applications that require high-performance vector search, scalable indexing, and real-time retrieval. By offering, the ...

Companies across every industry increasingly understand that making data-driven decisions is a necessity to compete now, in the next five years, in the next 20 and beyond. Data growth — unstructured ...

Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot, ...

In the age of generative AI (genAI), vector databases are becoming increasingly important. They provide a critical capability for storing and retrieving high-dimensional vector representations, ...

Qdrant's open-source vector database, known for its ability to handle billions of vectors, is now integrated into the Microsoft Azure cloud ecosystem allowing businesses to leverage Qdrant's powerful ...

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...

Couchbase on Tuesday launched a new version of its database platform, highlighted by improved vector indexing and retrieval capabilities aimed at making it faster to develop enterprise-grade AI ...