sqlite-vec
Decision gist · record as of 2026-08-14
Yes, if you need vector search in SQLite and accept the platform-wheel installation model. The package is actively maintained, permissively licensed, has no runtime dependencies, and is popular enough to indicate real-world usage. The main uncertainty is the unspecified Python version requirement and lack of documentation—verify compatibility with your Python version before committing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a platform-specific wheel match (macOS, Linux, or Windows); Python version requirement unspecified in package metadata.
- Medium install friction due to platform-specific wheels (macOS x86_64/arm64, Linux aarch64/x86_64, Windows amd64), but no runtime dependencies.
- Active maintenance with recent release activity.
License · maintenance · safety
permissive license (permissive) — Dual-licensed under MIT and Apache 2.0, both permissive licenses allowing commercial and private use with minimal restrictions.
last release 2026-03-31 (136 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 5,255,128 downloads/mo, #2,126 on PyPI
Alternatives
Verify before relying
pip install sqlite-vec
import sqlite_vec
# Vector search operations performed within SQLite queries- Whether the package requires a specific Python version (requires_python is unspecified in metadata)
- What vector operations and indexing strategies are supported
- Performance characteristics and scalability limits for vector search
- Integration requirements with existing SQLite installations
What it is and what it does
sqlite-vec is a SQLite extension that brings vector search and similarity operations to SQLite databases. It allows you to store embeddings and perform vector queries directly in SQL, eliminating the need for a separate vector database for simple use cases. The package is distributed as platform-specific wheels for macOS (both Intel and ARM), Linux (x86_64 and aarch64), and Windows, with no additional runtime dependencies beyond SQLite itself.
The extension is actively maintained and has achieved significant adoption, ranking in the top 5000 PyPI packages by downloads. It's designed for developers who want vector search capabilities without introducing external dependencies or complex infrastructure, keeping everything within the familiar SQLite ecosystem.
Use it for
- Add semantic search to SQLite-backed applications without deploying a separate vector database
- Store and query embeddings from language models or image encoders within existing SQLite schemas
- Build recommendation systems that use vector similarity on small to medium datasets
- Prototype AI features quickly by embedding vector operations directly in SQL queries
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need vector search in SQLite and accept the platform-wheel installation model.
The package is actively maintained, permissively licensed, has no runtime dependencies, and is popular enough to indicate real-world usage. The main uncertainty is the unspecified Python version requirement and lack of documentation—verify compatibility with your Python version before committing.
Install
sqlite-vec on PyPI
Before you install
Medium install friction due to platform-specific wheels (macOS x86_64/arm64, Linux aarch64/x86_64, Windows amd64), but no runtime dependencies. Active maintenance with recent release activity.
Requires a platform-specific wheel match (macOS, Linux, or Windows); Python version requirement unspecified in package metadata.
License in practice
Dual-licensed under MIT and Apache 2.0, both permissive licenses allowing commercial and private use with minimal restrictions.
Quickstart
pip install sqlite-vec
import sqlite_vec
# Vector search operations performed within SQLite queriesVerify before relying
- Whether the package requires a specific Python version (requires_python is unspecified in metadata)
- What vector operations and indexing strategies are supported
- Performance characteristics and scalability limits for vector search
- Integration requirements with existing SQLite installations
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 136 days since the last release |
| First released | |
| Downloads | 5,255,128 / month, #2,126 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: sqlite_vec-0.1.9-py3-none-macosx_10_6_x86_64.whl; sqlite_vec-0.1.9-py3-none-macosx_11_0_arm64.whl; sqlite_vec-0.1.9-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; sqlite_vec-0.1.9-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux1_x86_64.whl; sqlite_vec-0.1.9-py3-none-win_amd64.whl
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