Machine Learning & Data Science · head to head
Milvus vs Pinecone
Milvus
Machine Learning & Data Science
Open-source vector database for scalable similarity search
- From
- Free
- Rated
- -
Pinecone
Machine Learning & Data Science
Vector database for machine learning
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Milvus vector dimensions are capped at 32,768; Pinecone reads and writes are billed on separate meters, and reads are far more expensive, at $16 to $18 per million against $4 to $4.50 for writes on Standard
- They diverge on capability: Milvus covers Billion-scale vectors, Pinecone covers Vector similarity search.
Where they differ
Only the attributes on which Milvus and Pinecone actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
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
- Data partitioning
- PyTorch
- TensorFlow
- Linux support
- Mac support
Only in Pinecone
- Vector similarity search
- Metadata filtering
- Namespace partitioning
- Real-time updates
- OpenAI
- Cohere
Both cover
- Hybrid search
- Hugging Face
- LangChain
- LlamaIndex
- Web 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 Pinecone
- Storing and querying embeddings for retrieval augmented generationnot Pinecone
- Similarity search over images, audio or text at scalenot Pinecone
Pinecone
- Storing and querying vector embeddings for semantic searchnot Milvus
- Backing retrieval augmented generation over a document corpusnot 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
Pinecone
- Reads and writes are billed on separate meters, and reads are far more expensive, at $16 to $18 per million against $4 to $4.50 for writes on Standard
- Unit prices vary by region, so the same workload costs different amounts in different places
- The Standard plan carries a $50 monthly minimum and Enterprise $500, charged whether or not the usage reaches it
- Enterprise pays more per unit as well as more in minimum, at $24 to $27 per million reads against Standard's $16 to $18
- Indexes and namespaces are capped by plan, at 5 indexes on the free tier and 20 on Standard
- RBAC and SSO require the Standard plan
Pricing, plan by plan
Milvus
Free- Open SourceFree
- Full features
- Self-hosted
- Community support
- Zilliz CloudFree
- Managed service
- Free tier available
Pinecone
Free- FreeFree
- 1 index
- 100K vectors
- Standard$70/month
- Multiple indexes
- Higher capacity
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 Pinecone if
- You need vector similarity search.
- You want to start without paying.
- You also want metadata filtering.
Questions people ask
- Is Milvus or Pinecone better?
- Neither clearly leads. Milvus starts at Free and Pinecone at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Milvus or Pinecone?
- Milvus starts at Free and Pinecone at Free.
- Does Milvus or Pinecone run on more platforms?
- Milvus runs on Linux, Mac, Windows, Web. Pinecone runs on Web.
- 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 Pinecone is typically brought in for.
- What can Milvus do that Pinecone cannot?
- Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Data partitioning. Pinecone covers Vector similarity search, Metadata filtering, Namespace partitioning, Real-time updates. Both handle Hybrid search, Hugging Face, LangChain, LlamaIndex.