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SQLite-Vector

SQLite Vector is a cross-platform, ultra-efficient SQLite extension that brings vector search capabilities to your embedded database. It works seamlessly on iOS, Android, Windows, Linux, and macOS, using just 30MB of memory by default. With support for Float32, Float16, BFloat16, Int8, UInt8 and 1Bit, and highly optimized distance functions, it’s the ideal solution for Edge AI applications.

Installed by default in SQLite CloudGitHub: https://github.com/sqliteai/sqlite-vector

Highlights

No virtual tables required – store vectors directly as BLOBs in ordinary tables
Blazing fast – optimized C implementation with SIMD acceleration
Low memory footprint – defaults to just 30MB of RAM usage
Zero preindexing needed – no long preprocessing or index-building phases
Works offline – perfect for on-device, privacy-preserving AI workloads
Plug-and-play – drop into existing SQLite workflows with minimal effort
Cross-platform – works out of the box on all major OSes

Why Use SQLite-Vector?

Feature	SQLite-Vector	Traditional Solutions
Works with ordinary tables	✅	❌ (usually require special virtual tables)
Doesn’t need preindexing	✅	❌ (can take hours for large datasets)
Doesn’t need external server	✅	❌ (often needs Redis/FAISS/Weaviate/etc.)
Memory-efficient	✅	❌
Easy to use SQL	✅	❌ (often complex JOINs, subqueries)
Offline/Edge ready	✅	❌
Cross-platform	✅	❌

Unlike other vector databases or extensions that require complex setup, SQLite-Vector just works with your existing database schema and tools.

CLI

Getting Started

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