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 Cognee Builds AI Memory Layers with LanceDB
How Cognee uses LanceDB to deliver durable, isolated, and low-ops AI memory from local development to managed production.
Building Semantic Video Recommendations with TwelveLabs and LanceDB
Build semantic video recommendations using TwelveLabs embeddings, LanceDB storage, and Geneva pipelines with Ray.
Netflix’s Media Data Lake ❤️ LanceDB, CodeRabbit 💼 Case Study, Lance Namespace
Our September newsletter highlights LanceDB powering Netflix's Media Data Lake, a case study on CodeRabbit's AI-powered code reviews, and updates on Lance Namespace and Spark integration.
Setup Real-Time Multimodal AI Analytics with Apache Fluss (incubating) and Lance
Learn how to build real-time multimodal AI analytics by integrating Apache Fluss streaming storage with Lance's AI-optimized lakehouse. This guide demonstrates streaming multimodal data processing for RAG systems and ML workflows.
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.
Case Study: How CodeRabbit Leverages LanceDB for AI-Powered Code Reviews
How CodeRabbit leverages LanceDB-powered context engineering turns every review into a quality breakthrough.
LanceDB WikiSearch: Native Full-Text Search on 41M Wikipedia Docs
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.
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.
Columnar File Readers in Depth: Structural Encoding
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.