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

Vector database company Qdrant has released a dataset with 10 billion documents to help put large-scale vector search systems through their paces. Benchmarking these systems isn’t easy, particularly ...

The emergence of vector databases and vector search for handling massive quantities of complex data have radically transformed the way AI is implemented and managed. As a specialized approach for ...

DataStax, the well-funded Apache Cassandra-centric database company, is placing a lot of its current bets on AI and its technology’s ability to provide highly scalable vector search capabilities to ...

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

ScyllaDB on Tuesday launched vector search and storage capabilities in its X Cloud database platform. Vector search and storage are now fundamental to many AI pipelines because they enable enterprises ...

The semantic search capabilities added to the database offering include a new vector data type, vector indexes, and vector search SQL operators. Oracle is planning to add vector search capabilities to ...

With vector search now available in Enterprise Server and Community Edition, enterprises can streamline AI development and reduce operational overhead by avoiding fragmented stacks and external search ...

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 ...

News flash: Vector databases and vector searches are no longer a differentiation. Yes, how fast times change as what was cool just six months ago is suddenly table stakes! What is cool is a unified ...