Chang She - LanceDB: lightweight billion-scale vector search for multimodal AI | PyData Global 2023

LanceDB is an open-source, in-process vector database optimized for billion-scale vector search and multimodal AI applications

Key technical advantages:

• Uses Lance columnar format optimized for fast random access
• 100x faster performance vs Parquet/ORC for AI workloads
• GPU acceleration for indexing
• Zero-copy schema evolution
• Native integration with Arrow ecosystem (Pandas, Polars, DuckDB)

Production-ready features:

• Lightweight transactions
• Versioning and rollbacks
• Time travel capabilities
• Concurrent writes
• Secondary indices
• Separation of compute and storage

Flexible deployment options:

• Can run directly in application process
• Supports S3, EBS, EFS storage
• Self-hosted on Kubernetes/VMs
• Cloud version in development

Optimized for multimodal data:

• Images, videos, text, point clouds
• Multiple vector columns
• Rich metadata filtering
• Hybrid vector and full-text search
• Built-in model registry for embeddings

Cost-effective solution compared to other vector databases:

• Open source reduces licensing costs
• Single node architecture simplifies operations
• Direct S3 integration for cost-optimized storage
• Easy migration with 2-line conversion from existing formats