Lance Format

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..

The C binding to Lance.

Spark integrations for working with Lance datasets

Manage Multimodal Agentic Context Lifecycle with Lance

Lance Namespace is an open specification for describing access and operations against a collection of tables in a multimodal lakehouse

Browse Lance tables from your local machine in a simple web UI. No database to set up. Mount a folder and go.

The lance extensions for DuckDB enable reading and writing of lance tables.

Apache Flink Connector for Lance Vector Database

Integration between Lance and Ray for distributed data processing

Lance Namespace Implementations - Apache Hive, Apache Polaris, Apache Gravitino, Unity Catalog, AWS Glue and more