llama-index-vector-stores-lancedb
llama-index vector_stores lancedb integration
Decision gist · record as of 2026-08-14
Yes, if you are building a LlamaIndex application and prefer LanceDB as your vector store. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive MIT license. Verify that tantivy's dependencies align with your deployment environment before committing to production use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports current versions up to <4.0).
- Low install friction with a pure-Python wheel.
- Actively maintained as of the latest release.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects.
last release 2026-03-12 (155 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 73,500 downloads/mo, #14,987 on PyPI
Alternatives
Verify before relying
pip install llama-index-vector-stores-lancedb
from llama_index.vector_stores.lancedb import LanceDBVectorStore
vector_store = LanceDBVectorStore(db_path="./lancedb")- Whether tantivy (a Rust-based full-text search library) requires a C/Rust build toolchain on the target system.
- Performance characteristics and scalability limits for typical RAG workloads.
- Whether LanceDB persistence and query capabilities are fully documented for this integration version.
What it is and what it does
This package bridges LlamaIndex and LanceDB, allowing developers to use LanceDB as the vector storage backend for semantic search and retrieval-augmented generation (RAG) applications. LlamaIndex is a framework for building context-augmented LLM applications, and this integration lets you store and query embeddings in LanceDB instead of other vector databases.
The package is a thin adapter layer that implements LlamaIndex's vector store interface for LanceDB. It depends on lancedb for the actual vector database, llama-index-core for the framework abstractions, pylance for type checking support, and tantivy for full-text search capabilities. It's actively maintained and carries no known security vulnerabilities.
Use it for
- Store embeddings from LlamaIndex document processing pipelines directly into LanceDB for semantic search.
- Build RAG applications that retrieve context from LanceDB before passing queries to an LLM.
- Integrate LanceDB as a drop-in vector store replacement in existing LlamaIndex workflows.
- Combine vector similarity search with full-text search using tantivy's capabilities alongside LanceDB.
- Persist embeddings locally or in a managed LanceDB instance for production retrieval systems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building a LlamaIndex application and prefer LanceDB as your vector store.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive MIT license. Verify that tantivy's dependencies align with your deployment environment before committing to production use.
Install
llama-index-vector-stores-lancedb on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained as of the latest release. Depends on lancedb, llama-index-core, pylance, and tantivy; no compiled system dependencies noted.
Requires Python 3.10 or later (supports current versions up to <4.0).
License in practice
MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects.
Quickstart
pip install llama-index-vector-stores-lancedb
from llama_index.vector_stores.lancedb import LanceDBVectorStore
vector_store = LanceDBVectorStore(db_path="./lancedb")Verify before relying
- Whether tantivy (a Rust-based full-text search library) requires a C/Rust build toolchain on the target system.
- Performance characteristics and scalability limits for typical RAG workloads.
- Whether LanceDB persistence and query capabilities are fully documented for this integration version.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packageslancedbllama-index-corepylancetantivy |
| Maintenance | Actively maintained 155 days since the last release |
| First released | |
| Downloads | 73,500 / month, #14,987 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: llama_index_vector_stores_lancedb-0.5.0-py3-none-any.whl
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See also lancedb · llama-index-vector-stores-qdrant · llama-index-vector-stores-azureaisearch · llama-index-vector-stores-chroma · llama-index-vector-stores-redis · llama-index-vector-stores-milvus · lance-namespace · llama-index-vector-stores-pinecone · llama-index-vector-stores-faiss · llama-index-storage-kvstore-postgres