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When a table is created with `pa.json_()` (PyArrow's JSON extension type), it is stored internally as `lance.json` (LargeBinary with `lance.json` extension metadata). Calling `table.add()` with `pa.json_()` data failed with: ``` RuntimeError: lance error: Append with different schema: `data` should have type json but type was large_binary ``` `build_field_exprs` in `rust/lancedb/src/table/datafusion/cast.rs` saw that the input field (`Utf8` with `arrow.json` metadata) differed from the table field (`LargeBinary` with `lance.json` metadata). Since `can_cast_types(Utf8, LargeBinary)` is true, it inserted a DataFusion `Utf8 → LargeBinary` cast. That cast preserved the input field's `arrow.json` extension metadata instead of adopting the table's `lance.json` metadata, so lance-core detected a schema mismatch and rejected the append. This adds a special case in `build_field_exprs`: when the input is `arrow.json` and the table field is `lance.json`, the expression is passed through unchanged. Lance-core's write path already handles the `arrow.json → lance.json` conversion (including JSONB encoding), so no DataFusion cast is needed. Fixes #3144 Continues #3291 from a fork (the original author's branch could not be pushed to). The original commits are preserved; an additional commit fixes the CI failures on that PR — formatting, a missing trait import, and read-back assertions that assumed binary storage when a lance.json column is read back as `Utf8`. 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: yunju.lly <yunju.lly@antgroup.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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⭐ Click here ⭐ to see how fast we're growing!
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.
Contributors
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