Key strengths
Multimodal data curation and deduplicationUnified vector, full-text, and hybrid search with SQL filtersFeature engineering with Python UDFs and automatic updatesTraining directly from curated data with up to 70% MFUScalable vector search up to 10 billion vectors
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Documentation & Developer Resources
LanceDB's technical capabilities are organized around the following core areas:
- Multimodal Data Curation & Deduplication — Ingest and clean multimodal datasets at scale, with built-in deduplication workflows.
- Unified Search — Execute vector, full-text, and hybrid search queries with SQL filters in a single interface, supporting indices up to 10 billion vectors.
- Feature Engineering — Define and apply Python UDFs (User-Defined Functions) against your data, with automatic updates as underlying data changes.
- Training Integration — Stream curated data directly into model training pipelines, achieving up to 70% MFU.
- Integrations — First-class connectors for DuckDB, LlamaIndex, CrewAI, Spark, and Hermes Agent enable LanceDB to slot into existing ML and data engineering stacks.