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

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 ...

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 ...

Oracle Corp.’s flagship database management system is now available as a cloud service. Oracle Database 23ai features vector search and more than 300 additional major features, with many focused on ...

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 ...

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 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 ...

SQL Server 2025 gives developers new ways to work with text, JSON, real-time data changes and AI-ready vector data. Microsoft MVP Leonard Lobel explains why he considers it the most significant SQL ...

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, ...