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An open-source library for creating, storing, and searching multimodal data and vector embeddings, supporting AI and ML workflows.
Deep Lake is a vector database designed as a data lake for AI, capable of storing and managing vector embeddings, text, images, and videos. It utilizes a tensor format for efficient querying and integration with AI algorithms, making it suitable for similarity search and machine learning workflows. It is open-source and tailored for handling unstructured and multimodal data, with seamless integration with frameworks like PyTorch and TensorFlow.
AnythingLLM is an open-source AI application that integrates with vector databases to facilitate storage and retrieval of embeddings, supporting various AI and LLM workflows.
Apache Arrow is a cross-language development platform for in-memory data that is commonly used to facilitate efficient integration between vector databases and machine learning frameworks. It provides a standardized format for data exchange that is useful for storing and querying high-dimensional vectors in AI applications.
Arroy is an open-source library for efficient similarity search and management of vector embeddings, useful in vector database systems.
A platform focused on transforming AI/ML operations with transparency, control, and cost optimization, including support for vector database tasks.
DocArray is an open-source Python library designed for representing, storing, and retrieving multimodal data, making it suitable for AI and machine learning workflows involving complex data types such as images, text, audio, and video.
BaseDoc, specifying fields for different modalities and types.DocVec and DocList collections, enabling bulk operations and efficient workflows.DocArray is open-source software and free to use under the Apache License 2.0.