lance-format/lance
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #4 among Computer Vision repositories tracked this week, and #4 over the last 30 days; #508 of 2,531 repositories GStars tracks this week (top 20%).
5 releases in the last 90 days, the latest 1 day ago, with 287 contributors on GitHub.
Peaked at #84 in the weekly ranking the week of Oct 19, its best in the past year.
Use Cases & Benefits
- Provides a modern columnar data format optimized for machine learning workflows and multimodal datasets with fast random access and vector search capabilities.
- Delivers 100x faster random access than Parquet while supporting zero-cost schema evolution, rich secondary indices, and seamless integration with popular data tools.
- Use for building high-performance search engines and feature stores that require efficient vector similarity search and data versioning.
- Use for large-scale machine learning training pipelines needing fast IO, shuffles, and compatibility with frameworks like PyTorch and DuckDB.
- Use for storing, querying, and inspecting complex nested data such as images, point clouds, and robotics sensor data with efficient filtering.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
**Modern columnar data format for ML. Convert from Parquet in 2-lines of code for 100x faster random access, zero-cost schema evolution, rich secondary indices, versioning, and more. ** Compatible with Pandas, DuckDB, Polars, Pyarrow, and Ray with more integrations on the way.
Download the sift1m subset
Convert it to Lance
Build the index
Search the dataset
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+337 stars over 89 days across 15 snapshot days; best day +10 on Aug 29.
Forks
891+121
Open issues
1.3K+107
Compared with peers in Computer Vision
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| mudler/LocalAI | 49.8K | +332 | 75 | 19 days ago |
| koharu-rs/koharu | 6.4K | +192 | 63 | 30 days ago |
| opendatalab/MinerU | 82.1K | +0 | 75 | 9 days ago |
| rohitg00/ai-engineering-from-scratch | 72.1K | +0 | 75 | 2 days ago |
| lance-format/lance | 7.2K | +0 | 75 | 1 day ago |
| aurelio-labs/semantic-router | 4.0K | +0 | 75 | today |
| Category median | 49.8K | +0 | 75 | — |
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