Milvus vs ZeusDB Vector Database

Milvus is an open-source vector database from Zilliz for GenAI and scalable vector search. It supports approximate-nearest-neighbor, filtered, range, hybrid, and full-text search, along with reranking, fetch, and query operations. Metadata filtering, sparse vectors, and index types including HNSW, IVF, FLAT, DiskANN, and SCANN are documented. Deployment choices are Milvus Lite as a Python library, Standalone as a single-machine server, and Distributed on Kubernetes. Documentation recommends Lite for up to a few million vectors, Standalone up to 100 million, and Distributed for 100 million to tens of billions. Lite can run locally without a cloud service for private or sensitive data; an online upgrade from Standalone to a cluster is not currently supported. Official interfaces include REST plus Python, Go, Java, Node.js, and C++ APIs or SDKs. C# is contributed by Microsoft and Rust is under development. Security documentation covers authentication, TLS for gRPC and REST, and role-based access control at collection, database, and instance levels. The Apache 2.0 software is free, and Zilliz Cloud is offered as a managed option.

ZeusDB Vector Database is a vector database for AI workloads including semantic search, retrieval-augmented generation, and recommendations. Its free, self-hosted Open Source plan provides a Python API and approximate nearest-neighbor search with HNSW graphs. Optional Product Quantization compresses vectors for memory efficiency. Metadata filtering is supported, and indexes, metadata, and quantized vectors can be saved and reloaded. Hybrid search is listed. Published wheels support Linux x86_64 and aarch64, macOS Apple Silicon, and Windows x86_64; the package page lists Python 3.10 through 3.14. LangChain and LlamaIndex integrations are available with vector-store filtering and persistence features. Hugging Face, Anthropic, OpenAI, and Semantic Kernel integrations are in development. ZeusDB lists an Enterprise plan with managed deployment, SSO, RBAC, audit trails, encryption, automated backups and restore, observability, SLAs, and priority support. The managed enterprise edition is in development. The company says it was founded and launched its first site in 2012.