MongoDB Inc. today said its search and vector search features that had previously been confined to its Atlas cloud platform are now available for self-managed deployments, including MongoDB Community ...

MongoDB enables millions of developers to securely build AI applications on any infrastructure, from local machines to on-premises data centers "According to a 2025 IDC survey, more than 74% of ...

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 ...

MariaDB’s use of vector embedding is native and not an add-on capability, which simplifies management and allows for a seamless integration with existing SQL operations. In addition to vector search, ...

Aerospike Inc., the real-time database built for infinite scale, speed, and savings, is debuting the latest version of Aerospike Vector Search, equipped with new indexing and storage capabilities.

Most vector search systems struggle with a basic problem: how to break complex documents into searchable pieces. The typical approach is to split text into fixed size chunks of 200 to 500 tokens, this ...

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...

Artificial intelligence startup Cohere Inc. today launched Embed 4, its latest AI model designed to provide embeddings for search and retrieval for AI applications such as assistants and agents.