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Milvus
PublishedLast updated
Milvus is an open-source vector database that handles billion-scale embeddings with GPU acceleration for AI-powered search and retrieval.
Reviewed profile
Quick verdict
Milvus is for AI teams that need open-source vector search at serious scale. It is not a scraper or extraction tool, so ingestion still has to come from elsewhere.
- Best for
- Large embedding collections
- RAG search pipelines
- Hybrid vector search
- Open-source search infrastructure
- Not ideal for
- Web scraping APIs
- Browser automation
- Lightweight local projects
- Last verified
- Jun 26, 2026
Key facts
- Repositorymilvus-io/milvus, written in GoGitHub
- Stars42.4k GitHub starsGitHub
- LicenseOpen sourceGitHub
- SDKsPython, JavaScript, Go, and Java SDKsProject docs
- LanguagesPython, JavaScript, Go, and Java supportProject docs
Compiled from public repository and package data; check Milvus documentation for current details.
Sources
github.com
Verified against the milvus-io/milvus repository and the PyPI package.
Milvus is a powerful, open-source vector database designed for billion-scale similarity search and AI applications.
Key Features:
- Billion-Scale Vectors - Store and query massive embedding collections with consistent low latency.
- GPU Acceleration - Leverage GPU-powered indexing for dramatically faster vector operations.
- Hybrid Search - Combine vector similarity with scalar filtering for precise retrieval.
- Multiple Index Types - Choose from IVF, HNSW, and other algorithms to optimize for your workload.
- Cloud-Native Architecture - Scale compute and storage independently in containerized deployments.
Whether you're building semantic search over scraped content, powering RAG pipelines, or clustering extracted data, Milvus provides the performance and scale your AI applications require.
Categories:
Features:
Vector SearchOpen SourceSelf-HostedMulti-Language SDKsGPU AccelerationHybrid Search
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