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Will Jones
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Bridges Lance's internal `metrics`-crate instrumentation (object store request counts, bytes, latency, errors, and throttles) into OpenTelemetry, in both the Python and Node bindings, with a shared adapter in the Rust core. This is the LanceDB counterpart to lance-format/lance#7537. ## Rust core (`rust/lancedb`) Two new, **off-by-default** features: - `metrics` — re-exports the [`metrics`](https://docs.rs/metrics) crate as `lancedb::metrics` and turns on Lance's object-store instrumentation. Install any `metrics`-compatible recorder to collect them. - `metrics-otel` — adds `lancedb::metrics_otel`, a pull-based adapter that installs a process-global recorder aggregating into lock-free cumulative storage and exposes a snapshot/catalog API (`register_metrics_recorder`, `metrics_catalog`, `snapshot_metrics`, `MetricPoint`/`MetricValue`/`MetricKind`/`MetricDescription`). Both bindings build on this. ## Python `lancedb.otel.instrument_lancedb_metrics()` registers each metric as an OpenTelemetry observable instrument on the given (or global) `MeterProvider`. Available via the `otel` extra (`pip install lancedb[otel]`), which pulls in only `opentelemetry-api` — the application supplies and configures the SDK. ## Node `instrumentLanceDbMetrics()` provides the equivalent wiring against `@opentelemetry/api`. This is the only public entry point; the underlying recorder/catalog/snapshot functions stay internal. Because OpenTelemetry has no asynchronous histogram instrument, histograms are exported Prometheus-style as `<name>_bucket` (with an `le` attribute), `<name>_count`, and `<name>_sum`. Only `_sum` carries the histogram's unit; `_bucket` and `_count` observe cumulative counts and are unitless. The adapter is enabled by default in the Python and Node builds, and off by default in the Rust crate. ## Notes - Requires Lance ≥ `v9.0.0-beta.19`, which ships the object-store metrics APIs (upstream lance-format/lance#7537, now merged). `main` is already on beta.19, so this is a single feature commit with no dependency bump. - Tests: 8 Rust unit tests, 3 Python tests, 2 Node tests, all covering the end-to-end object-store-metrics → OpenTelemetry path. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 4.8 (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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