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.
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.
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.
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.
Building the Future Together: Introducing Lance Community Governance
Announcing the formal governance structure for the Lance community, establishing clear pathways for contribution and leadership with a three-tier system of contributors, maintainers and PMC.
Productionalize AI Workloads with Lance Namespace, LanceDB, and Ray
Learn how to productionalize AI workloads with Lance Namespace's enterprise stack integration and the scalability of LanceDB and Ray for end-to-end ML pipelines.
Manage Lance Tables in Any Catalog using Lance Namespace and Spark
Access and manage your Lance tables in Hive, Glue, Unity Catalog, or any catalog service using Lance Namespace with the latest Lance Spark connector.
The Future of Open Source Table Formats: Apache Iceberg and Lance
Explore the future of open source table formats: apache iceberg and lance with practical insights and expert guidance from the LanceDB team.