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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools integrates with
Pinecone
vs
LangChain

Choose Pinecone when…

  • •You want managed, scalable vector search
  • •You don't want to run infra and need SLAs
  • •High availability and zero ops for vector DB matter

Choose LangChain when…

  • •You want a broad, flexible LLM orchestration toolkit
  • •You need integrations with many tools and data sources
  • •You're prototyping or exploring LLM app patterns
Field
Pinecone
LangChain
Category
LLM Infrastructure
Pipelines & RAG
Type
SaaS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
Standard: Usage-based
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Stars
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⭐ 93,000
Health
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●85 — Active
Trajectory
— not enough data
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Synced
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today

Pinecone

Fully managed vector database with serverless indexes. No ops overhead. The go-to managed option for production RAG.

LangChain

Most widely used framework for building LLM applications. Chains, agents, RAG pipelines, and deep integrations with 300+ tools.

Pinecone Website ↗
LangChain Website ↗GitHub ↗

Shared Connections (6)

LlamaIndexHaystackQdrantWeaviateChromapgvector

Only Pinecone (3)

LangChainMilvusturbopuffer

Only LangChain (23)

OpenHandsCrewAIAutoGenLangGraphSemantic KernelLangSmithPineconeLiteLLM
See full comparison in Explore →