mirror of
https://github.com/lancedb/lancedb.git
synced 2026-08-18 12:08:35 +00:00
Will Jones
ff50e698cf
Standard GitHub-hosted runners are free on public repos, so all Actions spend here is on the `*-8x-*` / `4x` larger runners. Measured over 30 days at current (post-Jan-2026) larger-runner rates, that is ~$1,400/mo, and `npm-publish` is ~70% of it. ## Changes **Fat LTO was forcing builds onto large runners.** `[profile.release]` in `.cargo/config.toml` sets `lto = "fat"` with `codegen-units = 1`, which is single-threaded and the peak-memory step. The macOS `npm-publish` build was 111 of its 113 minutes in one `napi build` step, making it the critical path of the whole publish pipeline. The ThinLTO override already applied to Windows now covers macOS too, and both Windows builds move from `windows-2025-8x-x64` to the free standard `windows-2025`. **The npm-publish cargo cache never existed.** There are zero caches with its key prefix. The key was static, so `actions/cache` (which only writes on a miss) could never refresh it, and a multi-GB release `target/` per target could never fit the repo's 10 GB budget anyway. Now caches only the crate registry, keyed on `Cargo.lock`. The docker builds also mounted `.cargo/registry/*` while the cache saved `.cargo-cache`, so containers re-downloaded the registry every run. **Cache eviction thrash.** Repo cache usage is 10.4 GB against GitHub's 10 GB cap, so every PR run evicted main's warm entries. `rust.yml` and `nodejs.yml` now restore everywhere but only save from `main`. **npm-publish moves to nightly + tags** instead of every push to main (~90/month). The cross-compiled targets do need watching, so `report-failure` now fires on scheduled runs, and dedupes onto an existing open issue rather than filing one per night. **rust.yml aarch64-pc-windows-msvc** cross-compiled its tests and then skipped them, paying full codegen and link cost for a compile check. `windows-11-arm` is now GA and free on public repos, so it builds and tests natively. Its test step also passes `--target` — without it cargo used `target/ci/` rather than `target/<triple>/ci/` and rebuilt the entire dependency graph a second time. **pypi-publish.yml had no concurrency group**, so force-pushes left a ~74 minute Windows job running. ## What is cost vs. wall-clock | Change | Cost | Wall-clock | |---|---|---| | Windows npm-publish → free runners | **−$570/mo** | slower per job (8→4 cores) | | npm-publish nightly | **−$125/mo** | — | | pypi-publish concurrency | small | — | | macOS ThinLTO | $0 (already free) | **−~50 min** per release | | rust aarch64 Windows native | $0 (already free) | **−~25 min** | | rust `--target` on test step | $0 | large, avoids a second full build | | rust-cache `save-if` | small | faster via real cache hits | ## Risks - The two Windows builds now have 4 cores instead of 8 and ~14 GB of free disk. If they fail, it is most likely disk rather than memory; fallback is `windows-2025-4x-x64`, which still halves that line. - `windows-11-arm` has a thinner toolset (choco/vcpkg/protoc under emulation) and this enables a test step that has never run, so it may surface real aarch64 failures. That is the point, but it is the change most likely to need iteration. - ThinLTO applies to published macOS and Windows binaries, typically within a few percent of fat LTO. Linux release builds are untouched. ## Follow-ups - `python.yml` `pydantic1x` (37 min) and `Doctest` (33 min) each rebuild the extension from source via `pip install -e .` with no Rust cache; they should consume the wheel the `linux` job already builds. Worth ~$235/mo and ~70 min of compute per run. Separate PR. - The three `ubuntu-2404-8x-x64` npm-publish builds (~$420/mo at the old cadence) are the remaining large-runner spend; `aarch64-unknown-linux-gnu` could run natively on free `ubuntu-24.04-arm`. Worth doing after this lands so the ThinLTO change can be validated first. - The wheel composite actions declare `python-minor-version` as required but never use it, and every caller omits it (actionlint warns). 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- 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
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