Havenask is an open-source distributed search engine with support for vector search, designed for large-scale AI and search applications.

Valkey is an open-source in-memory key-value data store that supports vector search operations, making it useful for AI and machine learning vector database workloads. It is also a specialized open-source vector database designed for efficient management and retrieval of high-dimensional vector data, offering advanced APIs and optimized storage for AI workloads.

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.

Marqo is an open-source neural search engine that leverages vector representations to enable semantic search over textual data. It abstracts vector database complexity and provides a high-level interface for building advanced search applications.

A library by Google Research for efficient vector similarity search, suitable for large-scale nearest neighbor applications in AI.

Vearch is a distributed vector search engine designed for AI-native applications, enabling scalable and efficient similarity search across large datasets.