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## Why Every MemWAL write and read resolves rows by the table's unenforced primary key, but `enable_memwal` accepted a table without one. The spec installed, and every MemWAL `merge_insert` then failed with "table has a MemWAL index but no unenforced primary key" until MemWAL was disabled. Lance's MemWAL initialization doesn't catch it: its key checks pass when there is no key. ## What changes `enable_memwal` refuses a spec on a table with no unenforced primary key, for every sharding mode, before anything is committed. The check runs against the dataset the spec is committed to; a key cannot be removed once set, and an overwrite or restore of the table conflicts with that commit. Servers that install specs through this method get the check too. The Rust doc on `Table::enable_memwal` now states the requirement; the Python and TypeScript docs already did. ## Tests - New `test_enable_memwal_requires_primary_key` (Rust and Python): unsharded, bucket and identity specs are all refused without a key, a refused spec leaves nothing installed, and the same table accepts a spec once a key is set. The Rust test fails with the check disabled. - Tests that installed a spec on a table without a key now declare one first (6 Rust, 3 Python). - `cargo nextest run -p lancedb --features remote --lib`: 1529 passed. `cargo clippy -p lancedb --features remote --tests --examples -- -D warnings` and `cargo fmt --check` are clean; no integration test or example installs a spec. - Python: `test_memwal_spec.py` and `test_merge_insert_lsm.py`, 43 passed; `ruff format` and `ruff check` are clean.
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!
⭐ 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
Stay in Touch With Us