ScyllaDB Vector Search
High-performance NoSQL database with vector search capabilities built on USearch library and shard-per-core architecture, storing vector embeddings alongside structured data in unified tables.
About this tool
Overview
ScyllaDB launched vector search and storage capabilities in January 2026, enabling organizations to store vector embeddings alongside structured data attributes in the same ScyllaDB table.
Features
- Vector search underpinned by USearch library
- Shard-per-core architecture for optimized resource allocation
- Unified storage of vectors and structured data
- High-performance distributed NoSQL foundation
- Scalable vector search capabilities
- Self-managed and cloud deployment options
Technical Architecture
- Built on ScyllaDB's shard-per-core architecture
- USearch integration via Rust extension
- Optimized for ScyllaDB's distributed design
- Combines NoSQL benefits with vector search
Deployment Options
- ScyllaDB Cloud with managed vector search
- Self-managed database deployment
- Multi-cloud support
Use Cases
- Applications requiring both structured and vector data
- High-performance semantic search
- Real-time recommendation systems
- Unified data platform for AI applications
Pricing
Based on ScyllaDB Cloud or self-managed deployment costs
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Information
Websitevector-search.scylladb.com
PublishedMar 10, 2026
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