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.
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.
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.
Use the Lance format as your lakehouse layer for retrieval, RAG and more, with the native Lance extension for DuckDB
Our December newsletter highlights Lance SDK v1.0.0, our upcoming Lance community sync, Wikisearch demo, and the latest product and community updates.
A practical definition of multimodal complexity, and how LanceDB’s Multimodal Lakehouse is built to address these challenges.
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.
Our November newsletter highlights Lance community governance, a deep dive on Lance and Iceberg, a demo of Netflix's multimodal search, previous talk recordings, and the latest product and community updates.
Great RAG comes from a tight iteration loop. Learn how to systematically improve each layer of your RAG system using Kiln and LanceDB.
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.