Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

When designing search systems, the decision to use keyword-based search, vector-based search, or a hybrid approach can significantly impact performance, relevance, and user satisfaction. Each method ...

MongoDB has cemented its status as a global leader in the database market, evolving well beyond its roots as a popular NoSQL ...

What is vector search and how is it transforming the search experience? Edo Liberty, CEO of Pinecone and former head of Amazon's AI lab, explains. We’ve been talking with search industry pros and ...

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...

Despite the aggressive cost claims and dramatic scale improvements, AWS is positioning S3 Vectors as a complementary storage tier rather than a direct replacement for specialized vector databases.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

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 ...

A vector is a set of numbers. It represents data in a format machines can understand. Think of it like turning a sentence into a point in space. Vector search is a modern technique for retrieving ...

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 ...