Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Today’s complex, unstructured data — text, images, audio and video — are ...

Vector databases power RAG, semantic search, recommendations, and memory. Learn how indexing, filtering, and hybrid retrieval ...

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 ...

Tiered multitenancy allows users to combine small and large tenants in a single collection and promote growing tenants to dedicated shards. Qdrant has released Qdrant 1.16, an update of the Qdrant ...

AI generates complex, multilayered data sets that traditional databases can't handle. Top vector databases in the market use their search capabilities to quickly sift through text and images. The ...

For a long time, vector databases were a bit of a niche product, but because they are uniquely suited to provide context and long-term memory to large language models, everybody in the database space ...

Vector databases enable semantic searches but might also store sensitive data. Learn how to build a vector database security ...

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 As the scale of enterprise AI operations ...

Vector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie. The proliferation of large language models (LLMs) and the ...

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, ...