Machine Learning · head to head
Milvus vs Orange

Milvus
Machine Learning
Open-source vector database for scalable similarity search
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Milvus vector dimensions are capped at 32,768; Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- They diverge on capability: Milvus covers Billion-scale vectors, Orange covers Visual programming.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Milvus and Orange actually diverge.
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 Orange
- Visual programming
- Data visualization
- Machine learning
- Text mining
- Bioinformatics
- Python
- scikit-learn
- PyQt
Both cover
- Linux support
- Mac support
- Windows support
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 Orange
- Storing and querying embeddings for retrieval augmented generationnot Orange
- Similarity search over images, audio or text at scalenot Orange
Orange
- Visual programming for data mining and machine learning workflowsnot Milvus
- Teaching data science without writing codenot Milvus
- Exploratory data visualisation and clustering on tabular datanot 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
Orange
- Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
- Orange add-ons may carry additional licensing requirements set in their own licence files
- Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
- The software is distributed without any warranty of merchantability or fitness for a particular purpose
Pricing, plan by plan
Milvus
Free- Open SourceFree
- Full features
- Self-hosted
- Community support
- Zilliz CloudFree
- Managed service
- Free tier available
Orange
Free- Open SourceFree
- Visual programming
- Machine learning
- Data visualization
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 Orange if
- You need visual programming.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data visualization.
Questions people ask
- Is Milvus or Orange better?
- Neither clearly leads. Milvus starts at Free and Orange at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Milvus or Orange?
- Milvus starts at Free and Orange at Free.
- Does Milvus or Orange run on more platforms?
- Milvus runs on Linux, Mac, Windows, Web. Orange runs on Linux, Mac, Windows.
- 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 Orange is typically brought in for.
- What can Milvus do that Orange cannot?
- Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Hybrid search. Orange covers Visual programming, Data visualization, Machine learning, Text mining. Both handle Linux support, Mac support, Windows support.
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.
SourceOrange: What is the cost of Orange Data Mining?
Orange Data Mining is free open-source software available for Windows, Mac, and other platforms. There are no subscription fees, licensing costs, or paid tiers.
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.
SourceOrange: How is Orange Data Mining funded?
Orange Data Mining is supported through optional voluntary donations. The project encourages donations from users who value the software to support bug fixes, new features, educational content, and infrastructure maintenance.
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.
SourceRelated pages
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- Milvus vs AWS SageMaker
- Milvus vs Azure Machine Learning
- Milvus vs DataRobot
- Milvus vs Pinecone
- Milvus vs Weaviate
- Milvus vs Ray
- Milvus vs Fal AI
- Milvus vs Jupyter
- Milvus vs Keras
- Milvus vs LangChain
- Milvus vs Weights & Biases
- Milvus vs Alteryx
- Milvus vs Anaconda
- Milvus vs Domino Data Lab
- Milvus vs DVC
- Milvus vs Semantic Kernel
- Milvus vs Weka
- Milvus vs MATLAB
- Milvus vs KNIME
- Milvus vs JMP
- Milvus vs RapidMiner
- Milvus vs Dask
- Milvus vs Groq
- Milvus vs Haystack
- Milvus vs IBM SPSS
- Orange vs Google Vertex AI
- Orange vs AWS SageMaker
- Orange vs Azure Machine Learning
- Orange vs DataRobot
- Orange vs Pinecone
- Orange vs Weaviate
- Orange vs Ray
- Orange vs Fal AI
- Orange vs Jupyter
- Orange vs Keras
- Orange vs LangChain
- Orange vs Weights & Biases
- Orange vs Alteryx
- Orange vs Anaconda
- Orange vs Domino Data Lab
- Orange vs DVC
- Orange vs Semantic Kernel
- Orange vs Weka
- Orange vs MATLAB
- Orange vs KNIME
- Orange vs JMP
- Orange vs RapidMiner
- Orange vs Dask
- Orange vs Groq
- Orange vs Haystack
- Orange vs IBM SPSS

