PortkeyvsPinecone

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Portkey

LLM APIs & Inference

AI gateway for reliable and fast LLM applications

Full review →Website ↗

Pinecone

Vector Databases

Managed vector database for machine learning

Full review →Website ↗
FeaturePortkeyPinecone
CategoryLLM APIs & InferenceVector Databases
PricingFree + Pro plansFree + Pro $70/mo
GitHub Stars
✓ More stars
6k
—
PlatformsWeb, DockerWeb
Key Features
  • ✓ AI gateway
  • ✓ Fallbacks
  • ✓ Load balancing
  • ✓ Caching
  • ✓ Observability
  • ✓ Vector search
  • ✓ Serverless
  • ✓ Metadata filtering
  • ✓ Namespaces
  • ✓ Real-time indexing
Pros
  • + Automatic fallbacks
  • + Load balancing
  • + Request caching
  • + Observability built-in
  • + Open-source gateway
  • + Fully managed (zero ops)
  • + Serverless architecture
  • + Fast query performance
  • + Simple API
  • + Free tier available
Cons
  • − Added infrastructure layer
  • − Learning curve
  • − Some features need Pro
  • − Latency overhead
  • − Expensive at scale
  • − Vendor lock-in
  • − Limited to vector operations
  • − No self-hosting option
Tags
gatewayreliabilityobservabilityapi
vector-dbmanagedcloudserverless

Want to compare different tools?

← Back to compare picker

Related Comparisons

Portkey vs Hugging Face →Pinecone vs Hugging Face →Portkey vs Qdrant →Pinecone vs Qdrant →Portkey vs ChromaDB →Pinecone vs ChromaDB →Portkey vs LiteLLM →Pinecone vs LiteLLM →Portkey vs Weaviate →Pinecone vs Weaviate →Portkey vs Fireworks AI →Pinecone vs Fireworks AI →