Qwak Vector Store

HAKES is a system designed for efficient data search using embedding vectors at scale, making it a relevant solution for vector database applications.

A multi-model AI database designed for high-throughput vector processing at scale, supporting real-time AI use cases with a patented Hybrid Memory Architecture and efficient infrastructure usage, capable of handling large volumes of data and concurrent users.

Apache Cassandra is a distributed NoSQL database that is adding native support for high-dimensional vector storage and approximate nearest neighbor search, making it a scalable choice for AI and vector search workloads.

A distributed vector database designed for scalable and efficient vector similarity search. It is purpose-built for handling large-scale vector data and search workloads.

Google Cloud Platform offers vector search as part of its Vertex AI suite, enabling scalable and integrated vector search capabilities for AI-driven applications.

KDB is a high-performance vector database supporting billion-scale vector search, with features aimed at enterprises needing large-scale vector storage and retrieval.