Machine Learning · head to head
Milvus vs Semantic Kernel

Milvus
Machine Learning
Open-source vector database for scalable similarity search
- From
- Free
- Rated
- -

Semantic Kernel
Machine Learning
Model-agnostic SDK for AI orchestration
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Milvus vector dimensions are capped at 32,768; Semantic Kernel steep learning curve for advanced features
- They diverge on capability: Milvus covers Billion-scale vectors, Semantic Kernel covers Multi-model support.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Milvus and Semantic Kernel actually diverge.
| Attribute | Milvus | Semantic Kernel |
|---|---|---|
| Pricing model | freemium | Open source, no pricing |
| Platforms | Linux, Mac, Windows, Web | Python, .NET, Java |
| Founded | 2017 | Unknown |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Milvus
- Billion-scale vectors
- Multiple index types
- GPU acceleration
- Hybrid search
- Data partitioning
- PyTorch
- TensorFlow
- Hugging Face
Only in Semantic Kernel
- Multi-model support
- Agent framework
- Multi-agent systems
- Plugin ecosystem
- Vector database integration
- Multimodal support
- Local model support
- Enterprise observability
What people use each for
The jobs each tool is most often brought in to do.
Milvus
- Self hosting a vector database for semantic searchnot Semantic Kernel
- Storing and querying embeddings for retrieval augmented generationnot Semantic Kernel
- Similarity search over images, audio or text at scalenot Semantic Kernel
Semantic Kernel
- Building enterprise AI applications with LLM integrationnot Milvus
- Creating multi-agent systems for complex workflowsnot Milvus
- Developing AI-powered chatbots and assistantsnot Milvus
- Implementing RAG systems with vector databasesnot Milvus
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Milvus
- Vector dimensions are capped at 32,768
- A collection is limited to 64 fields, 1,024 partitions and 16 shards
- Only 1 index is allowed per field
- Search returns at most 16,384 vectors as top-k, and nq is capped at 16,384
- Input and output per RPC is capped at 64 MB for insert, search and query
- VARCHAR values are limited to 65,535 characters
- Data loaded into query nodes cannot exceed 90% of available memory
- An instance supports at most 65,536 collections
Semantic Kernel
- Steep learning curve for advanced features
- Documentation focuses on Azure cloud services
- Configuration complexity for multi-model scenarios
- Requires understanding of AI/LLM concepts
Pricing, plan by plan
Milvus
Free- Open SourceFree
- Full features
- Self-hosted
- Community support
- Zilliz CloudFree
- Managed service
- Free tier available
Semantic Kernel
Free- Open SourceFree
- MIT license
- Full framework access
- All language SDKs
Which should you pick?
Choose Milvus if
- You need billion-scale vectors.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want multiple index types.
Choose Semantic Kernel if
- You need multi-model support.
- You want to start without paying.
- You work on Python, .NET, Java.
- You also want agent framework.
Questions people ask
- Is Milvus or Semantic Kernel better?
- Neither clearly leads. Milvus starts at Free and Semantic Kernel at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Milvus or Semantic Kernel?
- Milvus starts at Free and Semantic Kernel at Free.
- Does Milvus or Semantic Kernel run on more platforms?
- Milvus runs on Linux, Mac, Windows, Web. Semantic Kernel runs on Python, .NET, Java.
- Can I use Milvus for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Milvus best used for?
- Milvus is most often used for self hosting a vector database for semantic search, storing and querying embeddings for retrieval augmented generation, similarity search over images, audio or text at scale. Of those, self hosting a vector database for semantic search and storing and querying embeddings for retrieval augmented generation are not what Semantic Kernel is typically brought in for.
- What can Milvus do that Semantic Kernel cannot?
- Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Hybrid search. Semantic Kernel covers Multi-model support, Agent framework, Multi-agent systems, Plugin ecosystem.
Answered from the vendors’ own pages
Milvus: How much does Milvus cost?
Milvus is open-source and free to use and modify. The self-hosted version has no licensing cost. Zilliz Cloud (the managed SaaS version) does not publish pricing on the website.
SourceSemantic Kernel: What LLM providers does Semantic Kernel support?
Semantic Kernel supports OpenAI, Azure OpenAI, Hugging Face, Nvidia, and other providers through extensible model implementations.
SourceMilvus: Is there a free or open-source version of Milvus?
Yes, Milvus is fully open-source and available for free. Milvus Lite is a lightweight option for learning and prototyping that can be installed via pip.
SourceSemantic Kernel: Can I run Semantic Kernel locally?
Yes. Semantic Kernel supports local models through Ollama, LMStudio, and ONNX for complete data control and offline operation.
SourceMilvus: Does Milvus offer a managed cloud service?
Yes, Zilliz Cloud is a fully managed Milvus cloud offering with serverless and dedicated cluster options. Pricing must be requested from the company as it is not listed on the public website.
SourceSemantic Kernel: Is Semantic Kernel free?
Yes. Semantic Kernel is MIT-licensed open source and completely free. You only pay for external LLM APIs you use.
SourceRelated pages
More on Semantic Kernel
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