Lancedb

LanceDB is an open-source, AI-native database designed for working with embeddings, unstructured data, and retrieval-augmented generation (RAG) workloads. It provides a persistent, local or cloud-backed vector store that integrates directly into your machine learning and application pipelines. The core purpose of LanceDB is to make it easy to store, index, and query high-dimensional vectors alongside rich metadata with low latency and efficient storage.

Built on the Lance columnar data format, LanceDB supports fast approximate and exact nearest neighbor search, scalable indexing, and efficient updates without complex infrastructure. It offers a simple API in Python, JavaScript/TypeScript, and other languages, enabling developers to create, query, and manage vector collections programmatically. The database supports hybrid search (combining vector similarity with metadata filters), versioning, and transactional semantics, making it suitable for production-grade AI systems. Its storage engine is optimized for SSDs and object storage, reducing both query time and storage costs while handling large-scale datasets.