Vector databases are the unsung heroes of the modern AI movement, storing unstructured data such as images, videos and text to enable people and systems to search uncategorized content. They are ...

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 ...

Data retrieval and embeddings enhancements from MongoDB set the stage for a year of specialized AI - SiliconANGLE ...

By releasing the code behind its search and vector engine under the SSPL, MongoDB is giving self‑managed users new visibility ...

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 ...

Hosted search and discovery platform for enterprise Algolia Inc. today launched NeuralSearch, a vector and keyword search engine using a single application programming interface that provides ...

When I first wrote “Vector databases: Shiny object syndrome and the case of a missing unicorn” in March 2024, the industry was awash in hype. Vector databases were positioned as the next big thing — a ...

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

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The race to develop the best search engine technology heated up again ...

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 ...

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 ...