LanceDB

LanceDB is an AI-native multimodal lakehouse built on the open source Lance format. It provides a unified platform for data curation, feature engineering, search & retrieval, and training at petabyte-to-exabyte scale. Users can find optimal distributions, deduplicate large datasets, build and scale features with Python UDFs, perform vector, full-text, and hybrid search with SQL filters, and train models directly from curated data with up to 70% Model FLOPS Utilization. The platform supports automatic versioning, branching, and rollback without data duplication. It is production-proven with support for over 100K queries per second and billions of rows in a single table. Trusted by companies like Coderabbit, Character.ai, Midjourney, Runway, World Labs, and Harvey, LanceDB eliminates data sync jobs and ad-hoc scripts, enabling faster iteration on AI model training lifecycles.

Key Benefits

• Unified platform for curation, feature engineering, retrieval, and training
• 10x faster data experimentation with automatic versioning and branching
• Production-proven at petabyte/exabyte scale with 100K+ QPS
• Supports vector, full-text, and hybrid search with SQL filters