Remote Python connections inherited the unsupported-operation stubs for `namespace_exists` and `table_exists`, so both raised `NotImplementedError` even when namespace and table operations worked. Add the missing remote overrides, async methods, and PyO3 bindings using the existing namespace describe and table open paths. Only an explicit not-found result returns `False`; permission, transport, and server errors propagate. This preserves authentication, dynamic headers, retries, and nested namespace handling, and rechecks cached tables before reporting that they exist. The async namespace helper also recognizes native `NamespaceNotFound` errors so missing local namespaces return `False`. The table and namespace guides document Python remote support and distinguish it from the unsupported `exists` routes used by direct REST namespace clients. Validation: - All 40 focused regression cases pass, covering successful and missing lookups, local and remote namespaces, dynamic headers, permission/server errors, invalid table identifiers, and cached tables that disappear. - The original inherited stubs reproduce the reported `NotImplementedError`; the local namespace regression reproduced the native missing-namespace `RuntimeError` before its fix. - Full remote connection suite: 255 passed. Local namespace tests: 14 passed. - `cargo clippy --quiet -p lancedb-python --features remote --lib`, `cargo fmt --all`, Python Ruff lint, and Python formatting checks pass. - Root `ruff check .` reports 48 existing errors in documentation examples under `docs/web-tests`; the Python subtree passes and those unrelated files are unchanged. Fixes #4722 <!-- lance-gatekeeper-fix:v1 agent=4d369a0681756fdb5a8b35853d7f5607 generation=1 --> --------- Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
The Multimodal Lakehouse for AI
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors
The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
Demo: Multimodal Search by Keyword, Vector or with SQL
Star LanceDB to get updates!
Key Features:
- Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
- Comprehensive Search: Support for vector similarity search, full-text search and SQL.
- Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
- Advanced Features: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
Products:
- LanceDB Embedded (open source): 100% open source, runs in your application's process; your data can live on local disk or in object storage. No vendor lock-in.
- LanceDB Enterprise: Production-scale distributed search, indexing, and maintenance. Plus, complete data sovereignty and security.
Ecosystem:
- Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
- Seamless Integration: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
- Rich Ecosystem: Integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
How to Install:
Follow the Quickstart doc to set up LanceDB locally.
API & SDK: We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|---|---|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/rest |
Join Us and Contribute
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.
Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.

