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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
Haystack
vs
Pinecone

Choose Haystack when…

  • •You're building search-first or RAG pipelines in Python
  • •Deepset's enterprise search DNA fits your use case
  • •You need flexible document processing pipelines

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
Field
Haystack
Pinecone
Category
Pipelines & RAG
LLM Infrastructure
Type
OSS
SaaS
Free Tier
✓ Yes
✓ Yes
Plans
deepset Cloud: Custom
Standard: Usage-based
Stars
⭐ 18,000
—
Health
●85 — Active
—
Trajectory
— not enough data
— not enough data
Synced
7 days ago
—

Haystack

deepset's open-source framework for building production NLP and LLM pipelines. Strong focus on RAG, search, and document AI use cases.

Pinecone

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

Haystack Website ↗GitHub ↗
Pinecone Website ↗

Shared Connections (3)

LangChainLlamaIndexQdrant

Only Haystack (1)

Pinecone

Only Pinecone (6)

HaystackWeaviateMilvusChromapgvectorturbopuffer
See full comparison in Explore →