Netflix's Media Data Lake and the Rise of the Multimodal Lakehouse
How Netflix built a Media Data Lake powered by LanceDB and the Multimodal Lakehouse to unify petabytes of media assets for machine learning pipelines.
How Netflix built a Media Data Lake powered by LanceDB and the Multimodal Lakehouse to unify petabytes of media assets for machine learning pipelines.
Learn how to build scalable feature engineering pipelines with Geneva and LanceDB. This demo transforms image data into rich features including captions, embeddings, and metadata using distributed Ray clusters.
No more Tantivy! We stress-tested native full-text search in our latest massive-scale search demo. Let's break down how it works and what we did to scale it.
Access and manage your Lance tables in Hive, Glue, Unity Catalog, or any catalog service using Lance Namespace with the latest Lance Spark connector.
Deep dive into LanceDB's dual structural encoding approach - mini-block for small data types and full-zip for large multimodal data. Learn how this optimizes compression and random access performance compared to Parquet.
Our August newsletter features a new case study with Dosu, recaps from events with Harvey and Databricks, and the latest product and community updates.
Is it worth the hype? Comparing Amazon S3 Vectors and LanceDB for RAG and agentic systems.
How Dosu uses LanceDB to transform codebases into living knowledge bases with real-time search and versioning.
LanceDB's June 2025 newsletter covering latest company news, product updates, open source releases, and community highlights.