Milvus
Milvus is a flexible, open-source vector database built for local and hybrid cloud deployment. With support for IVF, HNSW, and DiskANN, it provides the widest indexing variety for tuning performance on large-scale workloads. Milvus is ideal when you want control, configurability, and low infrastructure cost. If you want to compare the best vector databases for your data, try Agentset.
Vector Databases Are Just One Piece of RAG
Agentset gives you a managed RAG pipeline with the top-ranked models and best practices baked in. No infrastructure to maintain, no vector database to operate.
Trusted by teams building production RAG applications
Deployment
Self-Hosted, Managed Cloud
Cost
Free (self-hosted), infra cost only
Index Types
IVF, HNSW, DiskANN
Deployment
Infrastructure Options
Deployment Types
- Self-Hosted
- Managed Cloud
Cloud Providers
- Any
Strengths
What Milvus Does Well
- Widest variety of index types (IVF, HNSW, DiskANN, SCANN)
- Highly configurable for performance optimization
- Excellent for very large-scale deployments (trillions of vectors)
- Open-source with no licensing costs
- Strong performance when properly tuned
- Multiple similarity metrics supported
- Can deploy anywhere (any cloud or on-premise)
- Active CNCF project with strong backing
- GPU acceleration support
Weaknesses
Potential Drawbacks
- Steeper learning curve and more complex setup
- Requires more tuning and expertise to optimize
- API less intuitive than newer alternatives
- Documentation can be overwhelming for beginners
- Self-hosted requires significant infrastructure knowledge
- Higher operational overhead
Use Cases
When to Choose Milvus
Ideal For
- Large-scale deployments with billions/trillions of vectors
- Teams with infrastructure expertise wanting control
- Projects requiring specific index optimization
- Cost-sensitive applications at scale
- Research and experimentation with different algorithms
- GPU-accelerated workloads
Not Ideal For
- Quick prototypes or MVPs
- Small teams without infrastructure experience
- Projects needing simple plug-and-play solutions
- Teams wanting fully managed services
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with fully managed vector storage and retrieval. Upload your data, call the API, and get accurate results from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}Compare Databases
See how it stacks up
Compare Milvus with other vector databases to understand the differences in deployment options, cost, and features.
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