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Discover Milvus Hosting, the scalable vector database designed for AI applications. Enhance your data management and accelerate your AI projects today.
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Here’s a clear, detailed comparison of Milvus, ChromaDB, and Qdrant — three leading vector databases designed for similarity search and AI-native applications.
|
Feature / Capability
|
Milvus
|
ChromaDB
|
Qdrant
|
|---|---|---|---|
| Overview | High-performance vector DB optimized for scale and cloud-native deployments | Lightweight vector DB focused on simplicity and integration with LLM apps | Scalable vector search engine with rich filtering, payload support |
| Main Use Case | Production-grade vector search at scale | Prototyping, local LLM apps, embeddings | LLM RAG apps, hybrid filtering, real-time search |
| Performance | Very fast indexing & search, supports HNSW, IVF, and GPU-accelerated Faiss | Good for small to mid-scale apps | Fast, low-latency search with filtering and quantization |
| Data Storage | On-disk + in-memory hybrid (RocksDB or S3 backend) | In-memory (optional persistence via duckdb) | On-disk, SSD-optimized |
| Scalability | Excellent – supports cluster mode (via etcd, Pulsar, MinIO) | Limited – mostly local or dev use | Good – horizontal scaling and clustering support |
| Vector Index Types | IVF, HNSW, GPU-accelerated Faiss, DiskANN | Only HNSW (simplified options) | HNSW, PQ, SQ, Flat, Binary support |
| Filtering Support | Yes (limited in early versions, now improving) | Basic (few metadata filters) | Rich filtering (metadata + payload) |
| Hybrid Search (text + vector) | Basic support with reranking logic | None (unless you build it) | Excellent (filtering + scoring hybrid) |
| Language Bindings | Python, Java, Go, REST, C++ | Python (built for LangChain, LlamaIndex) | Python, REST, gRPC, TypeScript |
| Deployment Options | Docker, K8s, Bare Metal, Cloud | Local (pip install chromadb) | Docker, K8s, Cloud |
| GPU Support | ✅ Yes (optional Faiss GPU acceleration) | ❌ No | ❌ No (CPU only) |
| Open Source License | Apache 2.0 | Apache 2.0 | Apache 2.0 |
| Monitoring & Observability | Prometheus/Grafana integration | No native support | Prometheus-compatible metrics |
| Ease of Use | Medium (complex setup for cluster) | Very easy (pip install, Python-native) | Easy with Docker/K8s |
| Community & Ecosystem | Large (by Zilliz, backed by LF AI) | Growing, LangChain/LlamaIndex focus | Active, with REST/gRPC SDKs & docs |
Milvus is widely adopted by companies, researchers, and developers building AI-native applications, especially those requiring vector similarity search. Below are some of the main groups and organizations using Milvus!
Text/image/audio similarity search, RAG
Product, content, and user recommendation
Facial authentication, biometric ID
Reverse image search, semantic product search
Medical image retrieval, diagnosis support
Fraud detection, anomaly detection
Voice assistants, photo classification
Vector store for embedding-based search (RAG)
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