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Daniel Rammer
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Four of the eight LSM methods are remote-only in the core: `impl BaseTable for NativeTable` implements only set/unset/get_lsm_write_spec and close_lsm_writers, while flush_lsm, compact_lsm and get_lsm_stats fall through to trait defaults returning NotSupported. That is why Node had bound the four that work locally and stopped, and why the remaining four had no binding-level coverage anywhere. Node: add napi bindings for flush_lsm, compact_lsm, checkpoint_lsm and get_lsm_stats, with typed LsmStats/BucketStats/GenerationStats/ MemtableStats objects mirroring the existing LsmWriteSpec object in the same file. Tests assert each binding reaches the core and surfaces NotSupported locally; behavior against a real endpoint stays covered by the mocked-endpoint tests in rust/lancedb/src/remote/table.rs. Python: LsmWriteSpec was importable only from the private lancedb._lancedb -- it appeared in table.py solely under `if TYPE_CHECKING:`. Export it as lancedb.LsmWriteSpec, add it to __all__, and list it in the API reference, which had no mention of it and so rendered it nowhere. Java: add the LSM routes to lancedb-core. Java reaches LanceDB purely over REST through the generated namespace client, and these routes are not in the Lance Namespace spec, so they are issued through a small dedicated client. LsmWriteSpec is deliberately not org.lance.memwal. InitializeMemWalParams: that type defaults to maintaining no indexes where a spec here defaults to maintaining every index, and it cannot express the null that asks the server to resolve the set. checkpointLsm is ported from rust/lancedb/src/table/checkpoint.rs with its constants and status semantics intact -- 429/503 retried in place, 421 restarting from flush. Note: `mvnw spotless:apply` cannot run on JDK 21 (google-java-format 1.7, pinned in java/pom.xml, predates JDK 16's compiler API change). This is pre-existing and reproduces on a pristine main checkout; the Java sources here were formatted by hand to the checkstyle rules. Co-Authored-By: Claude Opus 5 (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.
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