The Excellence
Directory Platform Template

Milvus Distributed is a horizontally scalable, distributed deployment of the Milvus vector database designed for enterprise workloads, offering high reliability and the ability to handle billions of vectors with a comprehensive management toolkit.

ParlayANN is a scalable and deterministic parallel graph-based approximate nearest neighbor (ANN) search library. It provides parallel algorithms and implementations for high-dimensional vector similarity search, suitable as a core search component in large-scale vector database and retrieval systems.

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.

AstraDB (also known as Astra DB by DataStax) is a cloud-native vector database built on Apache Cassandra, supporting real-time AI applications with scalable vector search. It is designed for large-scale deployments and features a user-friendly Data API, robust vector capabilities, and automation for AI-powered applications.

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.

DiskANN is a graph-based approximate nearest neighbor search (ANNS) system optimized for fast and accurate billion-point nearest neighbor search on a single node, leveraging SSD storage. It is highly relevant for large-scale vector database applications requiring efficient vector search at scale.

Elasticsearch is a distributed search engine supporting various data types, including vectors, and provides scalable vector search capabilities, making it a popular choice for modern AI-powered applications. It can be extended with the k-NN plugin to provide scalable vector search using HNSW and Lucene, enabling hybrid semantic and keyword search capabilities.

Epsilla is an open-source vector database optimized for high-performance similarity search and scalable storage of vector embeddings.

FAISS (Facebook AI Similarity Search) is a popular open-source library for efficient similarity search and clustering of dense vectors. Developed by Facebook/Meta, it supports billions of vectors and is widely used to power vector search engines and databases, especially where raw speed and scalability are needed.

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

A cloud-native vector database management system designed for efficient storage and retrieval of vector embeddings. Directly relevant as a vector database platform.

Milvus is a mature, open-source vector database maintained by Zilliz, supporting large-scale similarity search with multiple indexing strategies and GPU acceleration. It includes variants such as Milvus Lite (lightweight version), Milvus Standalone (single-machine deployment), and Milvus Distributed (Kubernetes-based deployment for large scale).