ScyllaDB Vector Search is built on ScyllaDB’s shard-per-core architecture with a Rust-based extension that leverages the USearch approximate-nearest-neighbor (ANN) search library. The architecture ...

Oracle Corp. today is rolling out the latest version of its Exadata database-optimized computing platform, claiming 55% better performance on vector searches used in artificial intelligence model ...

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 ...

In the dynamic world of generative AI, efficient data management and processing is critical. Zilliz Cloud, a fully managed vector database platform, has introduced the Cardinal vector search engine, ...

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 ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...