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.

Vector databases (DBs), once specialist research instruments, have become widely used infrastructure in just a few years. They power today's semantic search, recommendation engines, anti-fraud ...

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 ...

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 ...

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 ...

Microsoft used Ignite 2025 to push Azure Cosmos DB further into AI search and agentic workflows, highlighting new capabilities aimed at developers building retrieval-heavy applications and multi-agent ...