How We Added Geospatial Support To Lance With No New Code
How Lance's Arrow-native architecture enables first-class geospatial support through extension types, GeoDataFusion integration, and R-Tree indexing.
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Branching and Shallow Cloning in Lance: Towards a "Git for AI Data"
A deep dive into how table formats handle version management for ML/AI experimentation, and how Lance unifies branching, tagging, and shallow clone on top of its multi-base architecture.
Lance × Hugging Face: A New Era of Sharing Multimodal Data on the Hub
Announcing native read support for Lance format on Hugging Face Hub. You can now distribute your large multimodal datasets as a single, searchable artifact (including blobs, embeddings and indexes) all in one place!
Rethinking Table File Paths with Uber: Lance’s Multi-Base Layout
A tour of Lance's file path design, and how Lance’s new multi-base layout enables multi-location datasets (such as Uber’s multi-bucket setup) with minimal metadata rewrites.
Keep Your Data Fresh with CocoIndex and LanceDB
Store a multimodal dataset of recipes in LanceDB, a multimodal lakehouse for AI, and keep it fresh with CocoIndex, a declarative data transformation framework for AI with incremental processing capabilities.
Lance × DuckDB: SQL for Retrieval on the Multimodal Lakehouse Format
Use the Lance format as your lakehouse layer for retrieval, RAG and more, with the native Lance extension for DuckDB
One System, Many Workloads: Rethinking What "Multimodal" Means for AI
A practical definition of multimodal complexity, and how LanceDB’s Multimodal Lakehouse is built to address these challenges.
Announcing Lance SDK 1.0.0: What This Milestone Means for the Community
We’re excited to announce that the core Rust SDK and the Python and Java binding SDKs are graduating to version 1.0.0, alongside a new, community-driven release strategy.
From BI to AI: A Modern Lakehouse Stack with Lance and Iceberg
A comparison of where Iceberg and Lance sit in the modern lakehouse stack. We highlight emerging architectures that are bridging the worlds of analytics and AI/ML workloads using these two formats, while being built on the same data foundation.