Closes #4288. Blob reads in Node can now be cancelled. `BlobFile.read`, `readRange` and `readRanges`, and `Table.fetchBlobs` and `fetchBlobFiles` take an optional `{ signal?: AbortSignal }` (new `BlobReadOptions` type). When the signal aborts, the call rejects with `signal.reason` (an `AbortError` unless the caller gave a reason) and the native future is dropped, so the read stops instead of running to completion. A signal that is already aborted rejects before any read starts. How it works: - On the Rust side, these five methods are now sync `#[napi]` methods that return `env.spawn_future(...)`. The future is wrapped in `futures::future::abortable`, and the abort handle is registered with napi's `AbortSignal::on_abort`. napi's `AbortSignal` is `Rc`-based, so it can't be an argument of an `async fn`, which is why the methods changed shape. The TypeScript signatures are unchanged apart from the new optional argument. - napi-rs installs its own `onabort` on the signal it receives, which would overwrite a handler the caller set. So the TypeScript wrapper passes a private `AbortController` signal to the native call for each request, forwards the caller's abort to it with `addEventListener(..., { once: true })`, and removes the listener when the call settles. Tests in `table.test.ts`: - an already aborted signal rejects on all five methods, and the handle still reads afterwards - a custom abort reason is what the call rejects with - a read with a signal that never aborts returns normally and leaves no `abort` listener on the signal - aborting a 32 MiB `readRange` right after it starts rejects with `AbortError`, and the same handle reads again afterwards The Node docs under `docs/src/js` are regenerated. I didn't add a test for where the `read()` cursor ends up after a mid-flight abort on a local table. The remote `BlobFile` documents that a cancelled read leaves the cursor unchanged, but I haven't confirmed the same for the native Lance handle, so the docs don't claim it.
The Multimodal AI Lakehouse
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
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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:
- Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
- Cloud and Enterprise: Production-scale vector search with no servers to manage. 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.
