July 10th, 2024

Vectorlite: Fast Vector Search for SQLite

Vectorlite is a runtime-loadable extension for SQLite enabling fast vector search with hnswlib on Windows, MacOS, and Linux. It supports SIMD acceleration, various distance types, and customizable HNSW parameters. Installation via `pip install vectorlite-py` in Python is suggested for usage. The GitHub page offers examples, API references, benchmarks, and more for detailed exploration.

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Vectorlite: Fast Vector Search for SQLite

The GitHub URL contains information about Vectorlite, a runtime-loadable extension for SQLite that facilitates fast vector search using hnswlib on Windows, MacOS, and Linux. Vectorlite offers features like calculating vector distances, creating virtual tables for vector storage, inserting and querying vectors, and identifying nearest neighbors. It supports SIMD accelerated vector distance calculation, various distance types, and allows customization of HNSW parameters for optimization. To utilize Vectorlite, users can install it via Python using the command `pip install vectorlite-py`. The content on the GitHub page includes examples, API references, benchmarks, quick start guides, build instructions, known limitations, and acknowledgments. For a detailed insight into Vectorlite and its functionalities, exploring the provided content is recommended.

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By @sejtnjir - 5 months
Exactly what I was looking for! Creating small, portable llm-powered tools begs for a lightweight vector database.

The other open source solution I found is sqlite-vec, which is still in alpha.