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Jack Ye
794fa023cd
Expose aggregate CPU, memory, and GPU budgets plus GPU-class placement
on materialized-view refreshes in Python and Rust. Forward options
through SQL and reject invalid or unsupported Embedded requests instead
of silently dropping constraints.
```python
job = view.refresh_async(
cpu_millis=8000,
memory_bytes=16 * 1024**3,
gpu_count=2,
gpu_class="h100",
)
job.wait()
```
```sql
REFRESH MATERIALIZED VIEW curated_training_set
WITH (cpu_millis = 8000, memory_bytes = 17179869184,
gpu_count = 2, gpu_class = 'h100');
```
The same options apply to blocking refreshes, async Python connections,
and the Rust refresh builder. CPU/memory budgets require all three
resource fields; GPU-only caps and class-only placement are also
supported. These are execution-wide caps and require a supporting
Enterprise server with an isolated execution backend. A cap does not
increase refresh parallelism; current MV refreshes use at most one GPU.
Updates API documentation and SQL reference, with Python sync/async and
Rust remote-submission regression coverage. Formatting and Python lint
pass; local builds and tests are intentionally skipped.
The Linux CI build and example steps explicitly select the LanceDB
package, matching the feature-test step. This avoids rebuilding and
retaining a second dependency graph after a workspace-wide build, which
exhausted runner disk space on both this branch and main.
Related: [ENT-3386](https://linear.app/lancedb/issue/ENT-3386)
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:
- LanceDB Embedded (open source): 100% open source, runs in your application's process; your data can live on local disk or in object storage. No vendor lock-in.
- LanceDB Enterprise: Production-scale distributed search, indexing, and maintenance. Plus, 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