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Lance is a versioned columnar data format and storage engine designed as a multimodal AI lakehouse. It serves as a vector database storage engine and a cloud object store dataset manager, organizing images, video, audio, and embeddings into a unified format optimized for machine learning workflows. The project distinguishes itself by combining a columnar layout for structured data with a specialized blob store for large multimodal tensors. It implements a hybrid search engine that integrates vector similarity search, full-text search, and SQL analytics on a single dataset, supported by a stor
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
zvec is an embedded vector database engine and indexing library designed for high-dimensional similarity search. It functions as a hybrid search engine and a retrieval-augmented generation knowledge base, allowing for the storage and retrieval of dense and sparse vectors. The system is distinguished by its hybrid retrieval pipeline, which fuses vector similarity, full-text keyword matching, and scalar metadata filtering into single query operations. It supports a plugin-based model integration system for registering custom embedding models and rerankers, as well as language bindings for nativ
Infinity is a distributed vector database and multimodal vector store designed to manage large-scale datasets for retrieval and similarity search. It serves as a backend for large language model applications and retrieval augmented generation pipelines by storing and retrieving dense vectors, sparse vectors, and full-text data. The system functions as a hybrid search engine, combining vector embeddings and full-text search with reranking algorithms to identify the most relevant documents. It supports multimodal data storage, allowing the maintenance of diverse data types including tensors, st
Lance is a columnar data format and storage layer designed for high-performance random access and the persistence of multimodal data. It functions as a vector database storage system, a multimodal data store, and a versioned dataset manager.
The main features of lance-format/lance are: Multimodal Data Storage, Dataset Versioning Systems, Columnar Storage Engines, Schema Evolution, Hybrid Search Engines, Hybrid Vector and Full-Text Search, Apache Arrow-Based Formats, Manifest-Based File Tracking.
Projects with overlapping indexed features include: eto-ai/lance — Lance is a versioned columnar data format and storage engine designed as a multimodal AI lakehouse. It serves as a… lancedb/lancedb — LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector… alibaba/zvec — zvec is an embedded vector database engine and indexing library designed for high-dimensional similarity search. It… infiniflow/infinity — Infinity is a distributed vector database and multimodal vector store designed to manage large-scale datasets for… qdrant/qdrant — Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors… apache/pinot — Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It…