ScyllaDB Brings Massive-Scale Vector Search to Real-Time AI

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 ...

ScyllaDB Releases Integrated Vector Search: 1B Vectors with 2ms P99s and 250K QPS Throughput

ScyllaDB today announced the general availability of its new Vector Search capability, which is integrated into ScyllaDB X Cloud. This high-performance vector search supports the industry’s largest ...
Nasdaq

MongoDB Extends Search and Vector Search Capabilities to Self-Managed Offerings

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 ...
TMCnet

MongoDB Continues to Grow with Vector Database Market Thriving

MongoDB has cemented its status as a global leader in the database market, evolving well beyond its roots as a popular NoSQL platform. Its adaptability and forward-thinking strategy continue to ...
Forbes

Propositional Chunking For Better Vector Search

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 ...