Software · head to head
Pinecone vs Weaviate
The short version
- Each has a real cost: 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; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: Pinecone covers Vector similarity search, Weaviate covers Vector and keyword search.
Where they differ
Only the attributes on which Pinecone and Weaviate actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Unknown), founded (2019).
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 Pinecone
- Vector similarity search
- Metadata filtering
- Namespace partitioning
- Real-time updates
Only in Weaviate
- Vector and keyword search
- Built-in vectorizers
- GraphQL API
- Multi-tenancy
- Linux support
- Mac support
- Windows support
Both cover
- Hybrid search
- OpenAI
- Cohere
- LangChain
- LlamaIndex
- Hugging Face
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Pinecone
- Storing and querying vector embeddings for semantic searchnot Weaviate
- Backing retrieval augmented generation over a document corpusnot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot Pinecone
- Generating and storing embeddings alongside the objects they describenot Pinecone
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Weaviate
- The free tier caps at 100,000 objects, 1 GB of memory and a single collection
- Billing is per million vector dimensions rather than per record, so wider embeddings cost proportionally more for the same object count
- Premium is a prepaid contract starting at $400 a month rather than pay as you go
- Storage rates do not fall consistently with tier, and Premium Dedicated is $0.1505 per GiB against $0.12 on the cheaper Flex plan
- The Query Agent is metered separately, free to 1,000 requests a month and $30 a month plus overage beyond
Pricing, plan by plan
Pinecone
Free- FreeFree
- 1 index
- 100K vectors
- Standard$70/month
- Multiple indexes
- Higher capacity
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
Which should you pick?
Choose Pinecone if
- You need vector similarity search.
- You want to start without paying.
- You also want metadata filtering.
Choose Weaviate if
- You need vector and keyword search.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want built-in vectorizers.
Questions people ask
- Is Pinecone or Weaviate better?
- Neither clearly leads. Pinecone starts at Free and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Pinecone or Weaviate?
- Pinecone starts at Free and Weaviate at Free.
- Does Pinecone or Weaviate run on more platforms?
- Pinecone runs on Web. Weaviate runs on Linux, Mac, Windows, Web.
- Can I use Pinecone for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Pinecone best used for?
- Pinecone is most often used for storing and querying vector embeddings for semantic search, backing retrieval augmented generation over a document corpus. Of those, storing and querying vector embeddings for semantic search and backing retrieval augmented generation over a document corpus are not what Weaviate is typically brought in for.
- What can Pinecone do that Weaviate cannot?
- Pinecone covers Vector similarity search, Metadata filtering, Namespace partitioning, Real-time updates. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Hybrid search, OpenAI, Cohere, LangChain.