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Lance: The Open Lakehouse Format for Multimodal AI
Easily convert Parquet to Lance in just 2 lines of code for 100x faster random access, efficient vector indexing, and reliable data versioning. Seamlessly compatible with Pandas, DuckDB, Polars, PyArrow, and PyTorch, with more integrations on the way.

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Unlock the Power of AI with the Open Lakehouse Format

Introducing Lance — the cutting-edge open lakehouse format designed for multimodal AI. Lance optimizes performance and compatibility with industry standards, empowering your AI workflows.

Key Features:

  • Hybrid Search: Combine vector similarity and full-text search seamlessly.
  • Lightning-Fast: Achieve up to 100x faster random access compared to traditional formats.
  • Multimodal Data Support: Efficiently store and manage diverse data types like images, audio, and text.
  • Smart Data Evolution: Easily alter schemas without complete rewrites, perfect for ML feature engineering.
  • Zero-Copy Versioning: Embrace ACID transactions and automatic versioning effortlessly.

Why Choose Lance?

  • Eliminate the struggle of using multiple specialized systems for AI/ML tasks.
  • Experience rich ecosystem integrations with frameworks like Pandas, Spark, and DuckDB.

Ready to transform your AI projects? Explore Lance today! Share your experiences and engage with the community in our Discord. Let’s innovate together!

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