🚀 The Future of Data for AI: AI-Lakehouse + DuckLake in v0.1.4! Data integration for Artificial Intelligence just took a massive leap forward. The v0.1.4 release of ai-lakehouse now features native support for DuckLake! Since the core mission of ai-lakehouse is to bridge analytical data storage with the power of vectors (embeddings) and hybrid search for AI, the addition of DuckLake as a catalog backend is a total game-changer. 🧠 Vector Power Meets DuckLake Simplicity: Native & Ultra-Fast Vector Search: ai-lakehouse extends the analytical ecosystem to store vector representations of text, images, and audio. With DuckLake, you manage these embeddings and metadata directly within a lightweight SQL database (like DuckDB), while keeping the raw data files in Parquet. Hassle-Free Hybrid Search (FTS + Vectors): It is now incredibly simple to run hybrid queries combining traditional Full-Text Search (keyword-based) with Dense Vector Search (semantic similarity). All of this without having to manage a separate, complex vector database. Efficient, Local RAG Pipelines: If you are building Retrieval-Augmented Generation (RAG) applications for LLMs, this combination removes all infrastructure friction. You get to store your documents, metadata, and embeddings in an ACID-compliant, portable lakehouse with top-tier performance. Vector Versioning with Time Travel: Because DuckLake supports version control and Time Travel, you can easily track how your vector space evolved over time. This is critical for auditing AI models and ensuring experiment reproducibility. Zero-Cost, Serverless Vector Architecture: Forget paying for and maintaining expensive vector database clusters. The combined architecture of AI-Lakehouse and DuckLake runs serverless and locally, scaling seamlessly from your laptop to cloud object storage (S3/ADLS/GCS). The ultimate synergy of a flexible data lake, a transactional data warehouse, and a local vector database. 👉 Check out the v0.1.4 release notes and start building the next generation of AI applications today! github.com/ailake-io/ai-lakehouse