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Daniel Rammer
ab74aa620c
Aligns the LSM stats surface with the MemWAL naming settled upstream in lance-format/lance#7943 and #7957, where the persisted unit became an SSTable. Two terms in this API predate that pass. **Generation -> SSTable.** A `GenerationStats` describes one flushed MemTable, which is an SSTable. The generation *number* is kept — an SSTable is identified by its generation — so only the noun moved. **Bucket -> table shard.** Each entry is one MemWAL shard. "Bucket" names only the hash sharding transform, so it was wrong for `identity` and `year` sharding, which produce shards and no buckets at all. | Before | After | |---|---| | `GenerationStats` | `SsTableStats` | | `BucketStats` | `TableShardStats` | | `LsmStats.buckets` | `LsmStats.table_shards` | | `BucketStats.generations` | `TableShardStats.sstables` | | `include_generation_rows` | `include_sstable_rows` | | `newest_generation` | `newest_sstable_generation` | | `outstanding_generations` | `outstanding_sstables` | Applied across Rust, Python, TypeScript, and Java, including the `get_lsm_stats` JSON field names. `LsmWriteSpec::Bucket` and `num_buckets` are unchanged — those name the sharding transform, not the shard. ## Compatibility Breaking for the MemWAL LSM stats API, which is experimental and paired with a server that renames the same fields. The JSON keys `table_shards` and `sstables` must roll out together with the WAL server change. ## Validation - `cargo check -p lancedb --all-features`, `cargo fmt --all` - `ruff format --check` and `ruff check` on the touched Python - `biome check` on the touched TypeScript The typedoc markdown under `docs/src/js` was updated by hand, not regenerated: `npm run docs` needs the napi-built `./native` types. Worth running `npm run docs` on this branch to confirm the generator agrees. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01HgVf5C2yRbwK6pe1aMYkmg
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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